Miracle-dz/UniFAR-FTUs huggingface dataset:
What can insects teach us about hearing loss?

Over the last three decades, insects have been utilized to provide a deep and fundamental understanding of many human diseases and disorders. Here, we present arguments for insects as models to understand general principles underlying hearing loss. Despite ∼600 million years since the last common ancestor of vertebrates and invertebrates, we share an overwhelming degree of genetic homology particularly with respect to auditory organ development and maintenance. Despite the anatomical differences between human and insect auditory organs, both share physiological principles of operation. We explain why these observations are expected and highlight areas in hearing loss research in which insects can provide insight. We start by briefly introducing the evolutionary journey of auditory organs, the reasons for using insect auditory organs for hearing loss research, and the tools and approaches available in insects. Then, the first half of the review focuses on auditory development and auditory disorders with a genetic cause. The second half analyses the physiological and genetic consequences of ageing and short‐ and long‐term changes as a result of noise exposure. We finish with complex age and noise interactions in auditory systems. In this review, we present some of the evidence and arguments to support the use of insects to study mechanisms and potential treatments for hearing loss in humans. Obviously, insects cannot fully substitute for all aspects of human auditory function and loss of function, although there are many important questions that can be addressed in an animal model for which there are important ethical, practical and experimental advantages.
A Scoping Literature Review on Evidence-Based Strategies to Increase Cervical Cancer Screening

Previous reviews of strategies to increase cervical cancer screening are more than 10 years old, the U.S. continues to fall short of the Healthy People 2030 cervical cancer screening goal, and guidelines were revised in 2018, therefore an updated review of the existing literature is needed. We conducted a scoping review using electronic databases PubMed, Scopus, and Ovid Medline that included publication dates between 2012 and 2021 to answer the question, “Which strategies implemented in U.S. primary care settings have been most successful in increasing rates of cervical cancer screening since the 2012 US Preventative Services Task Force cervical cancer screening guidelines were published? ” We mapped findings to pre-specified implementation strategy categories. After initially identifying 399 articles, we excluded 350 due to duplicates or not meeting review criteria, leaving 49 articles for full review. We excluded 37 of these during full-text review and identified 2 additional articles from the manual search of reference lists for a total of 14 studies for abstraction. Eleven articles reported on strategies resulting in increased cervical cancer screening, and 3 did not. Clinic workflow re-design strategies showed the greatest promise in improving cervical cancer screening rates, education strategies for patients had mixed results, and quality management strategies were not effective. These findings suggest clinical workflow re-structures and patient education strategies can increase cervical cancer screening in primary care settings. Results are particularly important in settings that care for underserved populations, as these settings may need additional implementation strategies to decrease cervical cancer screening disparities.
Déterminants De L’Adoption Des Techniques De Lutte Contre L’Érosion Hydrique En Zone Cotonnière (Determinants of the Adoption of Control Techniques Against Water Erosion in the Cotton Zone of Cameroon)

French Abstract: Dans la zone cotonniere du Cameroun, la pression fonciere croissante a conduit a une augmentation des superficies cultivees et accentue l’erosion des sols causee par l’intensite des pluies sur des sols mal proteges. Depuis deux decennies, les amenagements antierosifs ont ete diffuses, mais peu d’etudes ont analyse les facteurs favorisant leur adoption. L’objectif de cette etude a ete d’identifier les facteurs qui ont influe sur l’adoption et l’intensite d’adoption des amenagements antierosifs par les agriculteurs. Une enquete a ete effectuee dans le cadre du projet Eau-Sol-Arbre (ESA) entre 2008 et 2009 aupres de 303 agriculteurs de la zone cotonniere. Les donnees de cette enquete ont ete analysees a l’aide d’un modele Tobit II. Les resultats ont montre que, parmiles variables etudiees, celles qui ont influence la decision d’adoption des amenagements antierosifs par les agriculteurs ont ete (a) l’âge des agriculteurs, (b) la perception des problemes d’erosion par l’agriculteur, (c) leur appartenance a un groupe (religion, ethnie), (d) la disponibilite en main d’œuvre et (e) la tenure fonciere. Les facteurs expliquant l’intensite de cette adoption par les agriculteurs ont ete le nombre d’annees ecoulees depuis leur adoption des amenagements et leur mode d’acces au foncier. Le niveau d’instruction n’a influe ni sur l’adoption ni sur l’intensite de cette adoption. Afin de mieux orienter les actions futures, les programmes de lutte contre l’erosion doivent tenir compte de ces resultats dans leurs methodes d’intervention, mais aussi dans les evaluations d’impacts socio-economiques.English Abstract: In the cotton zone of Cameroon, the increasing pressure on land has led to an increase in agricultural areas and increased soil erosion caused by rainfall intensity on poorly protected soils. For the last two decades, anti-erosion plans have been disseminated, but few studies have analyzed the factors promoting their adoption. The objective of this study was to identify the factors that influenced the adoption and the adoption intensity of anti-erosion plans by farmers. A survey from the Water-Soil-Tree project involving 303 farmers was carried out in the cotton zone between 2008 and 2009. Survey data were analyzed with Tobit Model II. Results showed that among the variables studied, those that impacted on farmers’ decision to adopt anti-erosion plans were (i) their age, (ii) their perception of erosion problems, (iii) their belonging to a group (religious, ethnic), (iv) labor availability, and (v) land tenure. Factors that explained the adoption intensity by farmers were the number of years since adopting the plans and their access mode to land. The educational level did not affect the adoption nor the adoption intensity. In future actions, erosion control programs should integrate these results in their intervention methods, but also in socio-economic impact assessments.
Climatic factors responsible for triggering phenological events in Manilkara hexandra (Roxb.) Dubard., a canopy tree in tropical semi-deciduous forest of Sri Lanka

Vegetative and reproductive phenological events of Manilkara hexandra (Roxb.) Dubard. were studied in a tropical semi-deciduous forest at Bundala National Park, Sri Lanka, in relation to climatic factors. Twenty one individuals of M. hexandra were observed for phenological studies for four years at fortnightly intervals. M. hexandra is a leaf-exchanging species which shows synchronous phenological events. Rainfall played a key role in major leafing events. However, leaf shedding also took place in the middle of the major rainy season (late November-December). Flower buds initiated immediately after leaf shedding and leaf bud breaking but blooming took place towards the end of the major rainy season. High soil moisture and relative humidity due to heavy rainfall, low air and soil temperatures, low wind velocity and low solar radiation levels provided optimal external environmental conditions for flowering. However, triggering of flowering took place due to the sudden drop of solar radiation and subsequent drop in air and soil temperatures which was maintained for more than 36 hours. Abortion of flowers and young fruits occurred due to sudden climatic variations such as drought or heavy rains. In the absence of such adverse environmental conditions, a large number of fruits may be produced, resulting in a mass fruiting event.
Draft genome sequence of the Saccharomyces cerevisiae SpyCas9 expressing strain IMX2600, a laboratory and platform strain from the CEN.PK lineage for cell-factory research

ABSTRACT The biobased-economy aims to create a circular biotechnology ecosystem to transition from a fossil fuel-based to a sustainable industry based on biomass. For this, new microbial cell-factories are essential. We present the draft genome of the CEN.PK-derived Saccharomyces cerevisiae SpyCas9 expressing strain (IMX2600), that serve as chassis of new cell-factories.
Logic of myth and action

The first White man, so runs the Ramkokamekra Canela myth, was Aukê, a miraculous Indigenous boy who ends up killed by his kin. He reappears as a farmer and offers the Canela access to shotguns and proper dishware. Yet infelicitous choices made by the Indigenous people themselves deprive them from obtaining wealth and power. A messianic movement arising in 1963 was predicated on a promise to reverse this inequality. White people would end up having to hunt in the forest while all kinds of commodities would be imparted to the Canela. The article argues that, in order to achieve such reversal of fortune, the messianic movement followed a script that can be shown to be a structural inversion of the myth of the origin of the White man. Thus, historical events could be fashioned by myth.
Research on phage λ: a lucky choice

ABSTRACT Bacteriophage λ is a paradigm in the field of gene regulation and one of the best-understood systems in genetic regulatory biology. A so-called Genetic Switch determines the mechanisms by which λ transitions to its dual lifestyles—lytic or lysogenic. When λ initiates the lysogenic lifestyle, the phage-encoded CI repressor binds cooperatively to multi-partite operators in a defined pattern that autoregulates repression of phage lytic promoters as well as activation of the lysogenic promoter. The study of this genetic switch and related earlier research on phage λ revealed the main principles of gene expression and regulation in molecular biology. This article describes the underlying molecular details of λ lysogeny, as it is currently understood.
Massive Trajectory Data Based on Patterns of Life

Individual human location trajectory and check-in data have been the driving force for human mobility research in recent years. However, existing human mobility datasets are very limited in size and representativeness. For example, one of the largest and most commonly used datasets of individual human location trajectories, GeoLife, captures fewer than two hundred individuals. To help fill this gap, this Data and Resources paper leverages an existing data generator based on fine-grained simulation of individual human patterns of life to produce large-scale trajectory, check-in, and social network data. In this simulation, individual human agents commute between their home and work locations, visit restaurants to eat, and visit recreational sites to meet friends. We provide large datasets of months of simulated trajectories for two example regions in the United States: San Francisco and New Orleans. In addition to making the datasets available, we also provide instructions on how the simulation can be used to re-generate data, thus allowing researchers to generate the data locally without downloading prohibitively large files.
Statistical Inference for Spatial Regionalization

The process of regionalization involves clustering a set of spatial areas into spatially contiguous regions. Given the NP-hard nature of regionalization problems, all existing algorithms yield approximate solutions. To ascertain the quality of these approximations, it is crucial for domain experts to obtain statistically significant evidence on optimizing the objective function, in comparison to a random reference distribution derived from all potential sample solutions. In this paper, we propose a novel spatial regionalization problem, denoted as SISR (Statistical Inference for Spatial Regionalization), which generates random sample solutions with a predetermined region cardinality. The driving motivation behind SISR is to conduct statistical inference on any given regionalization scheme. To address SISR, we present a parallel technique named PRRP (P-Regionalization through Recursive Partitioning). PRRP operates over three phases: the region growing phase constructs initial regions with a predefined cardinality, while the region merging and region splitting phases ensure the spatial contiguity of unassigned areas, allowing for the growth of subsequent regions with predefined cardinalites. An extensive evaluation shows the effectiveness of PRRP using various real datasets.
Introduction

American public benefit provision bears little resemblance to a safety net capable of preventing people from experiencing economic devastation. It is not a carefully planned machinery of complementary programs but individual threads of support, some of which connect, many of which do not. The increased need for public benefit provision during the COVID-19 pandemic has renewed national and state policy debates on the importance of a comprehensive system of public investment in children. This volume draws on perspectives from various academic disciplines, both to identify the public supports that children need to thrive and to analyze existing models of complementary public support provision that do benefit children. The persistence of individual program-based support provisions and administrative burdens make it difficult for the current system to operate as a comprehensive safety net, but recent innovations offer hope: these include the expansion of the Child Tax Credit and collaborations between public agencies and organizations that help integrate aspects of service delivery. Missing, however, is the political will at all levels of government to invest in an infrastructure of support.
Summarizing Trajectories Using Semantically Enriched Geographical Context

The proliferation of tracking sensors in today's devices has led to the generation of high-frequency, high-volume streams of mobility data capturing the movements of various objects. These movement data can be enriched with semantic contextual information, such as activities, events, user preferences, and more, generating semantically enriched trajectories. Creating and managing these types of trajectories presents challenges due to the massive data volume and the heterogeneous, complex semantic dimensions. To address these issues, we introduce a novel approach, MAT-Sum, which uses a location-centric enrichment perspective to summarize massive volumes of mobility data while preserving essential semantic information. Our approach enriches geographical areas with semantic aspects to provide the underlying context for trajectories, enabling effective data reduction through trajectory summarization. In the experimental evaluation, we show that MAT-Sum effectively minimizes trajectory volume while retaining a good level of semantic quality, thus presenting a viable solution to the relevant issue of managing massive mobility data.
Artificial General Intelligence for Human Mobility (Vision Paper)

This paper presents a visionary perspective on developing Artificial General Intelligence (AGI) in the field of human mobility research. Human mobility profoundly influences our daily lives, impacting transportation systems, urban planning, logistics, and healthcare. While AI methods have made significant advancements in addressing human mobility challenges, they often struggle with the complexity and dynamic nature of this domain. The limitations arise from the narrow focus of existing AI systems, lacking the ability to generalize and adapt to new situations. To overcome these limitations, there is a growing interest in developing AGI systems. This paper explores the potential of AGI to revolutionize human mobility research by enabling systems to understand, learn, reason, and adapt across diverse domains and tasks. To achieve this goal, we propose the Mobility Foundation Model (MFM) and the concept of an intermediate modality is further introduced as a means to bridge the gap between different mobility modalities and scales. The unified representation allows the MFM to effectively learn and integrate information from various modalities. We also present a novel MFM as Administrator paradigm for leveraging MFM in complex mobility tasks. We hope that this paper will provide novel insights and open new directions in human mobility research.
GTI: A Scalable Graph-based Trajectory Imputation

GPS-enabled devices, including vehicles, smartphones, wearable and tracking devices, as well as various check-in and social network data are continuously producing tremendous amounts of trajectory data, which are used consistently in many applications such as urban planning and map inference. Existing techniques for trajectory data imputation rely heavily on the existing maps to perform map-matching operations. However, modern applications such as map construction and map update assume no map exists. In this paper, we propose GTI - a scalable graph-based trajectory imputation approach for trajectory data completion. GTI relies on cross-trajectory imputation, as it exploits "mutual information" of the aggregated knowledge of all input sparse trajectories to impute the missing data for each single one of them. GTI can act as a pre-processing step for any trajectory data management system or trajectory-based application, as it takes raw sparse trajectory data as its input and outputs dense imputed trajectory data that significantly increase the accuracy of different systems that consume trajectory data. We evaluate GTI on junction-scale as well as city-scale real datasets. In addition, GTI is used as a pre-processing step in multiple trajectory-based applications and it boosts the accuracy across these applications compared with the state-of-the-art work.
Traffic Accident Hotspot Prediction Using Temporal Convolutional Networks: A Spatio-Temporal Approach

Predicting traffic accident hotspots is crucial for ensuring public safety, improving transport planning, and reducing transportation costs. Traditional deep learning models, such as Transformers and LSTMs, have been successful in this field but fail to integrate critical attributes essential for accurate prediction. To address these limitations, we propose utilizing a Temporal Convolutional Network (TCN), which efficiently learns spatial, temporal, and other external factors integral to accident hotspot prediction. Our proposed TCN architecture 1 demonstrate superior performance over state-of-the-art methods, offering valuable insights for proactive accident mitigation.
Traditional and Western knowledge systems used by smallholders: Harnessing synergies for improved household food security in rural Ghana

ABSTRACT The discourse on knowledge integration persists in research and development practice. The need for traditional and Western knowledge systems to work together to achieve sustainable agricultural development in Ghana’s rural areas has become evermore relevant to achieve household food security in the context of changing climate, declining soil fertility, and labour challenges. The authors examined the role of knowledge integration in shaping the food security outcomes of socially differentiated smallholders’ households in Kassena-Nankana Municipal District and the Kassena-Nankana West District in the Upper East Region of Ghana, where food insecurity prevalence is very high. Using mixed methods approach, they found that most low resource endowed households that were unable to combine traditional and Western farming methods were more likely to experience food insecurity than were other households. Farmers with higher resource endowments integrated knowledges from both traditional and Western systems leading to better yield outcomes. However, combining both knowledge systems did not guarantee automatic success due to intervening factors. The authors conclude that different categories of smallholders’ resource endowment significantly impacts the smallholders’ food security status, and recommend that policy and development programming should promote integration of traditional and Western farming knowledge systems to achieve sustainable food crop production.
Optimizing Presence Sensing Lighting for Energy Efficiency and User Behavioral Needs in Small Swedish Homes

ABSTRACT A hybrid workstyle is becoming more common post-COVID-19, and longer occupancy hours at home are increasing household electricity consumption. Small homes are regarded as a potential for improving energy efficiency in the residential sector, and a home consists of mixed-function spaces with dynamic occupancy behaviors. These underpin the opportunity to optimize presence sensing lighting in small homes for energy efficiency and user-behavioral needs. A comprehensive overview of presence sensing approaches, comparing four types of non-wearable sensors connected to home lighting is made. A bibliometric mapping of the reviewed literature visually reinforces a significant research gap that presence sensing studies were not connected to home lighting but inclined toward the commercial and institutional context. Next, a non-exhaustive example of commercially available presence sensing products applicable to residential lighting for small homes is analyzed, and their general characteristics and technologies are synthesized. The literature and product overview identified five significant product knowledge gaps. Incorporating the gathered information leads to the proposal of a conceptual flexible radar-based sensor (prototype design), addressing a wish list with three important criteria to optimize future presence sensing lighting in a mixed-function small home. Future radar sensing studies are expected to develop an anticipatory lighting system that processes real-time multi-user vital signals for smarter localized and personalized lighting options for (small) living environments.
Endangered Przewalski’s horse, Equus przewalskii, cloned from historically cryopreserved cells

Two endangered Przewalski’s horse stallions were cloned from fibroblast cells cultured and cryopreserved in 1980. These stallions are clones of a male that lived from 1975-1998 that pedigree analyses identified as a genetically valuable male for present-day conservation breeding. This is the first time that multiple healthy clones have been produced for an endangered species.
Correcting the TRMM rainfall product for hydrological modelling in sparsely-gauged mountainous basins

ABSTRACT This study developed a correction approach to improve the rainfall field estimation using the TRMM rainfall product in a sparsely-gauged mountainous basin. First, Thiessen polygons were generated to define the measurement domain of each raingauge. Second, the rainfall of TRMM pixels in each Thiessen polygon was corrected using a benchmark method based on the difference between the monthly rainfall estimated by a raingauge and the TRMM pixel that possessed a gauge station (referred to as a gauged pixel). Third, the rainfall values in the gauged pixels were adjusted to the weighted average value of the gauge rainfall and corrected pixel rainfall. Finally, the rainfall in the non-gauged TRMM pixels was corrected as the sum of two terms. The first term is the adjusted rainfall in the corresponding gauged pixel in the same Thiessen polygon, and the second term is the rainfall (after benchmark correction) difference between the current pixel and the gauged pixel. Our results indicate that the corrected rainfall data outperforms the original TRMM product in the simulations of moderate and low flows and outperforms the sparse raingauges in the simulations of both peak and low flows. EDITOR A. Castellarin; ASSOCIATE EDITOR S. Huang