We analysed 2,800 programs in Java and C for which we knew they are functionally similar. We checked if existing clone detection tools are able to find these functional similarities and classified the non-detected differences. We make all used data, the analysis software as well as the resulting benchmark available here.

There is interest in using social media content to supplement or even substitute for survey data. O’Connor et al. (2010) report reasonably high correlations between the sentiment of tweets containing the word “jobs” and survey-based measures of consumer confidence in 2008-2009. Other researchers report a similar relationship through 2011 but after that time it is no longer observed, suggesting such tweets may not be as promising an alternative to survey responses as originally hoped. But, it’s possible that with the right analytic techniques, the sentiment of “jobs” tweets might still be an acceptable alternative. We explore this possibility by attempting to strengthen the original relationship and then extending the most successful approaches to more recent years. We classify “jobs” tweets into categories whose content is related to employment and categories whose content is not, to see if sentiment of the former correlates more highly with a survey-based measure of consumer sentiment. We use five sentiment-scoring tools, calculate daily sentiment three different ways, and use a measure of association less sensitive to outliers than correlation. None of these approaches improved the size of the relationship in the original or more recent data. We discuss the possibility that weighting and better understanding why users tweet might help recover the original relationship between the sentiment of tweets and survey responses. However, despite the earlier promise of tweets as an alternative to survey responses, we find no evidence that the original relationship was more than a chance occurrence.

Understanding the mechanism shaping species assemblage is a fundamental goal in ecology. In the past two hypotheses have been suggested. One is the filtering hypothesis where environmental factors select for species of similar traits such that they co-occurring in similar niches. The other is the competitive exclusion hypothesis where related species are driven far apart by competition such that they over-disperse across different niches. Here, we investigate the relationship between species assemblage and their phylogenetic relatedness from the network perspective by using five different ecosystems ranging from oceans to an inland lake. We quantified the similarity in species'network positions in a food web and cluster them into different trophic role groups; and from an on-line database we quantified their phylogenetic distances. We then investigated whether related species tend to under or overdisperse across different trophic role groups. In general, our result suggests the environmental filtering process is the dominant force shaping the species assemblage of those ecosystems. However, there are some possible cases where related species are driven by competition such that they evolve to adopt different trophic roles in relatively closed ecosystems.

A complete list of live websites using the Showeblogin Facebook Page Like Box technology, compiled through global website indexing conducted by WebTechSurvey.

ABSTRACT Objective: This paper aims to verify the thermodynamic, mechanical and chemical properties of CuNiTi 35ºC commercial wires. Methods: Forty pre-contoured copper-nickel-titanium thermodynamic 0.017 x 0.025-in archwires with an Af temperature of 35°C were used. Eight wires from five different manufacturers (American Orthodontics® [G1], Eurodonto® [G2], Morelli® [G3], Ormco® [G4] and Orthometric® [G5]) underwent cross-sectional dimension measurements, tensile tests, SEM-EDS and differential scanning calorimetry (DSC) tests. Parametric tests (One-way ANOVA and Tukey post-test) were used, with a significance level of 5%, and Pearson’s correlation coefficient test was performed between the Af and chemical elements of the wires. All sample tests and statistical analyses were double-blinded. Results: All wires presented standard dimensions (0.017 x 0.025-in) and superelastic behavior, with mean plateau forces of: G1 = 36.49N; G2 = 27.34N; G3 = 19.24 N; G4 = 37.54 N; and G5 = 17.87N. The Af means were: G1 = 29.40°C, G2 = 29.13°C and G3 = 31.43°C, with p>0.05 relative to each other. G4 (32.77°C) and G5 (35.17°C) presented statistically significant differences between each other and among the other groups. All samples presented Ni, Ti, Cu and Al in different concentrations. Conclusions: The chemical concentration of the elements that compose the alloy significantly influenced the thermodynamic and mechanical properties.

A complete list of live websites using the Comments Like Dislike technology, compiled through global website indexing conducted by WebTechSurvey.

The Alternative Data Vendor market is experiencing robust growth, driven by the increasing demand for non-traditional data sources to enhance investment strategies and business decision-making. The market's expansion is fueled by the proliferation of digital data, advancements in data analytics, and a growing need for more comprehensive and nuanced insights across various sectors. The BFSI (Banking, Financial Services, and Insurance) sector remains a significant driver, leveraging alternative data for credit scoring, fraud detection, and risk management. However, growth is also witnessed in industrial, IT and telecommunications, and retail and logistics sectors as businesses seek competitive advantages through data-driven decision-making. The diverse types of alternative data, including credit card transactions, web data, sentiment analysis, and public data, cater to a wide range of applications. While data privacy and regulatory concerns pose challenges, the market is overcoming these hurdles through robust data anonymization and compliance strategies. The competitive landscape features both established players like S&P Global and Bloomberg, along with emerging technology-driven companies, fostering innovation and market expansion. We project a steady compound annual growth rate (CAGR) resulting in a substantial market expansion over the next decade. This growth is expected to be distributed across regions, with North America and Europe maintaining leading positions due to early adoption and developed data infrastructure. The forecast period from 2025 to 2033 anticipates continued market expansion, propelled by factors such as increasing data availability from IoT devices, refined analytical techniques, and expanding applications across new sectors. The market's segmentation by application and data type is expected to further evolve, with niche players focusing on specific data sets and industries. This specialized approach allows for deeper insights and catering to specific client needs. Geographic expansion will continue, with growth in Asia-Pacific particularly driven by the increasing adoption of digital technologies and expanding economic activity. Strategic partnerships and mergers and acquisitions will likely shape the competitive landscape, fostering consolidation and further innovation in alternative data solutions. Despite challenges related to data quality, security, and ethical considerations, the overall outlook for the Alternative Data Vendor market remains highly positive, with substantial growth opportunities over the long term.

The gut microbiome performs many important functions in mammalian hosts, with community composition shaping its functional role. However, the factors that drive individual microbiota variation in wild animals and to what extent these are predictable or idiosyncratic across populations remains poorly understood. Here, we use a multi-population dataset from a common rodent species (the wood mouse, Apodemus sylvaticus), to test whether a consistent “core” gut microbiota is identifiable in this species, and to what extent the predictors of microbiota variation are consistent across populations. Between 2014 and 2018 we used capture-mark-recapture and 16S rRNA profiling to intensively monitor two wild wood mouse populations and their gut microbiota, as well as characterising the microbiota from a laboratory-housed colony of the same species. Although the microbiota was broadly similar at high taxonomic levels, the two wild populations did not share a single bacterial amplicon sequence variant (ASV), despite being only 50km apart. Meanwhile, the laboratory-housed colony shared many ASVs with one of the wild populations from which it is thought to have been founded decades ago. Despite not sharing any ASVs, the two wild populations shared a phylogenetically more similar microbiota than either did with the colony, and the factors predicting compositional variation in each wild population were remarkably similar. We identified a strong and consistent pattern of seasonal microbiota restructuring that occurred at both sites, in all years, and within individual mice. While the microbiota was highly individualised, some seasonal convergence occurred in late winter/early spring. These findings reveal highly repeatable seasonal gut microbiota dynamics in multiple populations of this species, despite different taxa being involved. This provides a platform for future work to understand the drivers and functional implications of such predictable seasonal microbiome restructuring, including whether it might provide the host with adaptive seasonal phenotypic plasticity.

Imaging mass spectrometry (imaging MS) has emerged in the past decade as a label-free, spatially resolved, and multipurpose bioanalytical technique for direct analysis of biological samples from animal tissue, plant tissue, biofilms, and polymer films., Imaging MS has been successfully incorporated into many biomedical pipelines where it is usually applied in the so-called untargeted mode-capturing spatial localization of a multitude of ions from a wide mass range. An imaging MS data set usually comprises thousands of spectra and tens to hundreds of thousands of mass-to-charge (m/z) images and can be as large as several gigabytes. Unsupervised analysis of an imaging MS data set aims at finding hidden structures in the data with no a priori information used and is often exploited as the first step of imaging MS data analysis. We propose a novel, easy-to-use and easy-to-implement approach to answer one of the key questions of unsupervised analysis of imaging MS data: what do all m/z images look like? The key idea of the approach is to cluster all m/z images according to their spatial similarity so that each cluster contains spatially similar m/z images. We propose a visualization of both spatial and spectral information obtained using clustering that provides an easy way to understand what all m/z images look like. We evaluated the proposed approach on matrix-assisted laser desorption ionization imaging MS data sets of a rat brain coronal section and human larynx carcinoma and discussed several scenarios of data analysis.

We designed a human study to collect fixation data during visual search. We opted for a task that involved searching for a single image (the target) within a synthesised collage of images (the search set). Each of the collages are the random permutation of a finite set of images. To explore the impact of the similarity in appearance between target and search set on both fixation behaviour and automatic inference, we have created three different search tasks covering a range of similarities. In prior work, colour was found to be a particularly important cue for guiding search to targets and target-similar objects. Therefore we have selected for the first task 78 coloured O'Reilly book covers to compose the collages. These covers show a woodcut of an animal at the top and the title of the book in a characteristic font underneath. Given that overall cover appearance was very similar, this task allows us to analyse fixation behaviour when colour is the most discriminative feature. For the second task we use a set of 84 book covers from Amazon. In contrast to the first task, appearance of these covers is more diverse. This makes it possible to analyse fixation behaviour when both structure and colour information could be used by participants to find the target. Finally, for the third task, we use a set of 78 mugshots from a public database of suspects. In contrast to the other tasks, we transformed the mugshots to grey-scale so that they did not contain any colour information. In this case, allows abalysis of fixation behaviour when colour information was not available at all. We found faces to be particularly interesting given the relevance of searching for faces in many practical applications. 18 participants (9 males), age 18-30 Gaze data recorded with a stationary Tobii TX300 eye tracker More information about the dataset can be found in the README file.

The growth of the Internet since its inception has fueled strong demand and profitability for web design services, as both businesses and households increasingly conduct activities online. The pandemic accelerated this trend, forcing businesses to upgrade their digital presence amid lockdowns and remote work, which resulted in significant revenue gains for web designers in 2020. This trend continued in 2021 as the strong economic recovery boosted corporate profit and gave businesses greater funds to invest in the industry’s services. More recently, high inflation and rising interest rates have raised costs and curtailed demand, with some businesses opting for cheaper alternatives like templates rather than custom web design, contributing to a drop in revenue in 2022. Despite these challenges, rising stock prices linked to AI advancements pushed business income substantially upward, enabling further investment in web design through 2023 and 2024 and benefiting revenue. However, high inflation and rising interest rates have recently raised costs and curtailed demand, with some businesses opting for cheaper alternatives like templates rather than custom web design. In response to shifting client expectations, web designers now prioritize mobile-first design, rapid performance, personalization and interactive content. These adaptations, along with investments in new technologies, have allowed web designers—especially smaller ones—to differentiate themselves and sustain long-term growth. Overall, revenue for web design services companies has swelled at a CAGR of 2.3% over the past five years, reaching $47.4 billion in 2025. This includes a 1.5% rise in revenue in that year. Market saturation will limit revenue growth for website designers moving forward. With nearly all US adults now using the Internet, opportunities for finding new customers are dwindling as internet usage approaches universality. As a result, major providers may turn to mergers and acquisitions to maintain market share, while smaller companies will likely focus on niche markets or specific geographies to secure stable income. Additionally, tariffs imposed by the Trump administration could further restrain demand by increasing consumer prices, reducing disposable income and pushing the economy toward recession. In response, web designers may expand geographically to find new clients. Amid these headwinds, AI and automation technologies are transforming design workflows, increasing efficiency while fostering a greater need for skilled workers and enabling more tailored services. Companies are also adapting by prioritizing inclusivity and sustainability, attracting broader demographics and eco-conscious clients. Overall, revenue for web design services providers is forecast to inch upward at a CAGR of 1.1% over the next five years, reaching $49.9 billion in 2030.

This statistic shows the share of Deezer survey respondents who played music they like to their children in the United States in 2018. In that year, **** percent of respondents stated that they played music they like to their children.

Human modified environments are rapidly increasing, which puts other species in the precarious position of either having the ability to adapt to a new area or, if they are not able to adapt, they must move to a different area if able. It is generally thought that behavioral flexibility, the ability to change behavior when circumstances change, plays an important role in the ability of a species to rapidly expand their geographic range. Great-tailed grackles (Quiscalus mexicanus; GTGR) and their closest relative, boat-tailed grackles (Quiscalus major; BTGR) are social, polygamous species. The former is rapidly expanding their geographic range by settling in new areas, ​​whereas the latter are not. We previously found that GTGR are behaviorally flexible, however not much is known about BTGR behavior, which provides an ideal way to test the hypothesis that behavioral flexibility plays a key role in the GTGR rapid range expansion using the comparative method. We compared behavioral flexibility of GTGR from two populations across their range (an older population in the middle of the northern expansion front: Tempe, Arizona, and a more recent population on the northern edge of the expansion front: Woodland, California) with BTGR from Venus, Florida to investigate whether the rapidly expanding GTGR are more flexible. We found that both species, and both GTGR populations, have similar levels of flexibility (measured as food type switching rates during focal follows). Our results elucidate that, while GTGR are highly flexible, flexibility may not be the primary factor involved in their successful range expansion. If this were the case, we would expect to see a rapid range expansion in BTGR as well. This adds further support to our previous findings that persistence and flexibility variance play a larger role in the edge GTGR population. The evidence that two closely related species with similar levels of flexibility, but different range expansion rates does not support the hypothesis that flexibility is the primary facilitator of rapid geographic range expansions into new areas.

We report the infrared (IR) properties of planetary nebulae (PNe) with Wolf-Rayet (WR) type and wels central stars known to date and compare them with the IR properties of a sample of PNe with H-rich central stars. We use near-, mid-, and far-IR photometric data from archives to derive the IR properties of PNe. We have constructed IR colour-colour diagrams of PNe using measurements from 2MASS, IRAS, WISE, and Akari bands. [WR] PNe have a larger near-IR emission from the hot dust component and also show a tendency for stronger 12{mu}m emission as compared to the other two groups. Cool asymptotic giant branch dust properties of all PNe are found to be similar. We derived the dust colour temperatures, dust masses, dust-to-gas mass ratios, IR luminosities, and IR excess (IRE) of PNe for these three groups. [WR] PNe and wels-PNe tend to have larger mean values for dust mass when compared to the third group. The average dust-to-gas mass ratio is found to be similar for the three groups of PNe. While there is a strong correlation of dust temperature and IR luminosity with the age for the three groups of PNe, the dust mass, dust-to-gas mass ratios, and IRE are found to be non-varying as the PNe evolve. [WR] PNe and wels-PNe show very similar distribution of excitation classes and also show similar distribution with Galactic latitude. Cone search capability for table J/MNRAS/493/730/table2 (Nebular parameters derived for [WR] PNe) Cone search capability for table J/MNRAS/493/730/table3 (Nebular parameters derived for wels-PNe)

The object W33 is a giant molecular cloud that contains star forming regions at various evolutionary stages from quiescent clumps to developed HII regions. Since its star forming regions are located at the same distance and the primary material of the birth clouds is probably similar, we conducted a comparative chemical study to trace the chemical footprint of the different phases of evolution. We observed six clumps in W33 with the Atacama Pathfinder Experiment (APEX) telescope at 280GHz and the Submillimeter Array (SMA) at 230GHz. We detected 27 transitions of 10 different molecules in the APEX data and 52 transitions of 16 different molecules in the SMA data. The chemistry on scales larger than ~0.2pc, which are traced by the APEX data, becomes more complex and diverse the more evolved the star forming region is. On smaller scales traced by the SMA data, the chemical complexity and diversity increase up to the hot core stage. In the HII region phase, the SMA spectra resemble the spectra of the protostellar phase. Either these more complex molecules are destroyed or their emission is not compact enough to be detected with the SMA. Synthetic spectra modelling of the H_2_CO transitions, as detected with the APEX telescope, shows that both a warm and a cold component are needed to obtain a good fit to the emission for all sources except for W33 Main1. The temperatures and column densities of the two components increase during the evolution of the star forming regions. The integrated intensity ratios N_2_H^+^(3-2)/CS(6-5) and N_2_H^+^(3-2)/H_2_CO(4_2,2_-3_2,1_) show clear trends as a function of evolutionary stage, luminosity, luminosity-to-mass ratio, and H_2_ peak column density of the clumps and might be usable as chemical clocks. Cone search capability for table J/A+A/572/A63/list (List of FITS files) Associated data

Context: Kanye West Rap Verses (243 Songs, 364 Verses)
Content: All verses are separated by empty lines. The data has been cleaned to remove any unnecessary words or characters not part of the actual verses.
Acknowledgements: The lyrics are owned by Kanye West and his label, but the dataset was compiled by myself using Rap Genius.
Past Research: Ran the data through a RNN to try to generate new verses that sounded similar to Kanye's existing verses.
Inspiration: It'll be interesting to see what analysis people can do on this dataset. Although it's pretty small, it definitely seems like a fun dataset to mess around with.

Note: Below is a list of all the songs used for verse extraction. Songs labeled with (N) were excluded due to either not containing rap verses (only choruses), or me not being able to locate the actual lyrics.

Mercy
Niggas in Paris
Clique
Bound 2
No Church in the Wild
Father Stretch My Hand Pt. 1
New Slaves
Blood on the Leaves
Black Skinhead
Don't Like
Monster
All Day
Father Stretch My Hand Pt. 2
I Am a God
Famous
No More Parties in LA
I'm In It
Hold My Liquor
Facts
Power
Cold
New God Flow
Gotta Have It
Blame Game
Wolves
FML
Runaway
Can't Tell Me Nothing
Waves
Dark Fantasy
Gorgeous
Gold Digger
Devil in a New Dress
Otis
So Appalled
All Falls Down
Highlights
All of the Lights
On Sight
Who Gon Stop Me
Guilt Trip
Murder to Excellence
30 Hours
Send It Up
Through the Wire
Stronger
Illest Motherfucker Alive
Flashing Lights
Last Call
Homecoming
H·A·M
The Morning
Lost In The World
Saint Pablo
Freestyle 4
Feedback
Jesus Walks
Good Morning
The One
Good Life
Touch the Sky
Diamonds from Sierra Leone
Never Let Me Down
Big Brother
New Day
Hell of a Life
To the World
Hey Mama
Heard 'Em Say
White Dress
Heartless
Champion
That's My Bitch
Everything I Am
Gone
Made in America
I Wonder
Spaceship
Get Em High
Christian Dior Denim Flow
We Don't Care
Family Business
See Me Now
The Glory
Welcome to the Jungle
Looking For Trouble
Drive Slow
The Joy
The New Workout Plan
Champions
Love Lockdown
Primetime
We Major
Roses
School Spirit
Addiction
Lift Off
Barry Bonds
Bittersweet Poetry
Welcome to Heartbreak
Drunk and Hot Girls
Two Words Slow Jamz
Paranoid
Crack Music
Classic (Nike Air Force Remix)
RoboCop
Breathe In Breathe Out
Late
Bring Me Down
Christmas in Harlem
Celebration
Good Night
Lord Lord Lord
Chain Heavy
Eyes Closed
Don't Look Down
Take One for the Team
Mama's Boyfriend
Apologize
We Can Make It Better
When I See It
Because of You (Remix)
Home
Throw Some D's (Remix)
Livin' in a Movie
Another You
Impossible
Back Niggaz
Birthday Song
Back to Basics
Line for Line
What You Do To Me
In Common (Remix)
Pussy Print
Guard Down
Piss On Your Grave
Jukebox Joints
SMUCKERS
All Your Fault
Can't Stop
Drunk in Love (Remix)
Welcome to the World
Blazing
Glenwood
Ayyy Girl
We Fight We Love (Remix)
Anyone But Him
Erase Me
Diamonds (Remix)
Hate
Ego (Remix)
Alright
I'm the Shit (Remix)
Flight School
Teriya-King
Punch Drunk Love (The Eye)
Therapy
Digital Girl
Promise Land
It's Over
Go Hard
Beat Goes On
Everyone Nose
Down
In the Mood
Southside
My Drink n My 2 Step (Remix)
Still Dreaming
Tell Me When to Go (Remix)
Fly Away
They Say
Paid the Price
Call Some Hoes
The Way That You Do
Welcome Back (Remix)
Confessions Pt. 2 (Remix)
My Baby
Gettin' It In
I Changed My Mind
Selfish
Higher
Talk About Our Love
I See Now
Getting Out the Game
03 'til Infinity
So Soulful
Oh Oh
U Know
Candy
The Good, the Bad and the Ugly
Changing Lanes
The Bounce
Let's Get Married (Remix)
Pretty Girl Rock (Remix)
That Part
U Mad
Blessings
I Won
I Wish You Would
Marvin & Chardonnay
E.T.
Forever
The Big Screen
Supernova
Make Her Say
Run This Town
Gifted
Walkin' on the Moon
Knock You Down
Stay Up! (Viagra)
Put On
American Boy
Pro Nails
I Still Love H.E.R.
Wouldn't Get Far
Number One (With Pharrell)
Grammy Family
Extravaganza
Brand New
Wouldn't You Like 2 Ryde
This Way
Us Placers
Don't Stop!
Sanctified
Hurricane 2.0
Start It Up
In for the Kill (Remix)
Deuces (Remix)
Alors on Danse (Remix)
Live Fast Die Young
Maybach Music 2
Swagga Like Us (Remix)
Lollipop (Remix)
Plastic
Finer Things
Anything
Buy U a Drank (Remix)
This Ain't a Scene, It's an Arms Race (Remix)
Pusha Man
Selfish
Real Love
Hold On (Remix)

(N) Coldest Winter
(N) Ultralight Beams
(N) Only One
(N) I Love Kanye
(N) Why I Love You
(N) Fade
(N) Welcome to the Jungle
(N) Amazin...

Data accompanying the paper: Jeantet and Dufourq (2023). Empowering Deep Learning Acoustic Classifiers with Human-like Ability to Utilize Contextual Information for Wildlife Monitoring. Ecological Informatics. 77, 15749541, DOI: 10.1016/j.ecoinf.2023.102256

Our investigation contributes to the field of deep learning and bioacoustics by highlighting the potential for improved classification performance through the incorporation of contextual information such as time and location.

To test if spatial-temporal information can enhance deep learning classifier, we developed a subset dataset derived from Xeno-Canto that included location metadata as input alongside the spectrogram. We used this dataset with the primary purpose of creating a bird song classification task with species carefully selected to share similar vocal characteristics but from distinct geographical distributions. We only considered the recordings of category `A', corresponding to the best quality score in the database.

The dataset contains songs of 22 bird species from 5 families and genera differents. The recordings were downloaded from the Xeno-canto database in .wav format and each recording was manually annotated by labelling the start and stop time for every vocalisation occurrence using Sonic Visualiser. In total, database contained 6537 occurrences of bird songs of various length from 967 file recordings. A precise description of the distribution by species and country can be found in the associated article.

The audio files are provided in "Audio.zip" and the manually verified annotation in "Annotations.zip". The name of each file follows the following nomenclature: Family_genus_species_country of recording_date of recording_ID Xenocanto_type of song.wav/svl. The meta-data information of each file can be find in the csv file provided (Xenocanto_metadata_qualityA_selection) based on the number of the ID Xeno-canto. The annotations can be viewed using the Sonic Visualiser software. The python codes to process these files and train neural networks can be found here : github

The files were divided into a training folder and a validation folder to train and evaluate the efficiency of each method. For each species and country, we randomly selected 70% of the downloaded recordings for the training dataset and kept the remaining 30% for validation.

Process to select the species : We selected the ten most recorded families in the Passeriformes order, the most represented order in Xeno-canto database. From each of the ten families, we again sub-samples the ten most recorded genera. For each genus, we observed the countries of the recordings and the number of available recordings per species and countries. From these observations, we made a self-selection of genera containing species with similar songs but recorded in different regions, with enough recordings available by species and country to form a dataset . At the end, 5 genus were selected containing 22 species. We considered only recordings associated with bird songs, specifically, within Xeno-canto we selected the `song' type. To balance the number of recordings between species of the same genus, we reduced the number of recordings for the most represented species. Thus, for each genus we calculated the average of the number of records available per species and per country and limited the number of recordings for the species/country pairs that were in greater number to this value plus two.

1.Within natural communities, different taxa display different dynamics in time. Why this is the case we do not fully know. This thwarts our ability to predict changes in community structure, which is important for both the conservation of rare species in natural communities and for the prediction of pest outbreaks in agriculture.

2.Species sharing phylogeny, natural enemies and/or life history traits have been hypothesized to share similar temporal dynamics. We operationalized these concepts into testing whether feeding guild, voltinism, similarity in parasitoid community, and/or phylogenetic relatedness explained similarities in temporal dynamics among herbivorous community members.

3.Focusing on two similar data sets from different geographical regions (Finland and Japan), we used asymmetric eigenvector maps as temporal variables to characterize species- and community-level dynamics of specialist insect herbivores on oak (Quercus). We then assessed whether feeding guild, voltin...

The research project aims at understanding alternative food organizations' engagement for a more ecological, just and healthier food system. To do so, we developed a broad definition of alternative food organizations in order to capture the diversity of actors, actions and goals. We defined alternative food organizations as organizations that contest, counter, or reduce one or several of the mainstream food system's negative externalities (inequalities, ecological or health issues) or question the overall mainstream food system. Thanks to a mapping of all alternative food organizations in Geneva and a representative survey, we studied their goals and their concrete actions in favor of changing the current food system. Furthermore, a frame analysis of their websites allowed understanding how alternative food organizations talk about the problems of the food system as well as what solutions they propose.

Plants from Brazilian campos rupestres usually present morphological strategies that allow them to survive in extreme environments. However, in Chamaecrista (Leguminosae, Caesalpinioideae), one of the most diverse genera in the campos rupestres, needle-like leaflets are rare. Reviewing the species that present such leaf morphology, we describe Chamaecrista acicularis, a new species, from the Canastra Range, in the southwestern region of the state of Minas Gerais, Brazil. Phylogenetic analyses revealed that C. acicularis is not closely related to other quite similar needle-like leafleted species and that this trait evolved convergently. We also present comments on the phylogenetic relationships of needle-like leafleted species as well as the evolution of the leaflet amplitude, and a detailed description of C. acicularis alongside illustrations, photos, geographical distribution, a key to the needle-like leafleted species and taxonomic notes on similar species. Additionally, we expand the...