Miracle-dz/UniFAR-FTUs huggingface dataset:
The Optimized Analysis For Early Detection Of Skin Cancer Using Artificial Intelligence

: Skin cancer is the most common type of cancer in the globe and can be fatal if not diagnosed and treated in time. Early detection is the key for timely diagnosis and successful outcomes. Artificial Intelligence (AI) has emerged as a promising tool for early detection of skin cancer. AI algorithms can provide support in improve diagnosis accuracy through automated image analysis techniques such as pattern recognition and machine learning. AI systems also enable non-experts to assess the risk of skin cancer through image classification and segmentation. AI solutions can also automate manual processes like analyzing biopsied images, leading to quicker diagnosis and treatments with improved accuracy. By combining AI with conventional tools, providers can offer a cost-effective and efficient solution for skin cancer screening and diagnosis in healthcare settings. In this way, AI can help to reduce the burden of skin cancer on both lives and healthcare resources.
Report on Carcinogens (RoC) Concept: 1‐Bromopropane

1‐Bromopropane (CASRN 106‐94‐5) is a brominated hydrocarbon that is currently used as a solvent in a variety of industrial and commercial applications. 1‐Bromopropane has been selected as a candidate substance1 for the RoC due to the potential for substantial human exposure to 1‐bromopropane, and an adequate database to evaluate its potential carcinogenicity. Exposure to workers has been increasing in the past few years due to several new applications in which 1‐bromopropane has been substituted for substances identified as suspect carcinogens or ozone‐depleting chemicals. Occupational exposure data are available from several published studies and indicate that workers can be exposed to high levels of 1‐bromopropane. 1‐Bromopropane has been tested for carcinogenicity in rodents in a 2‐year inhalation study (NTP 2011a). In addition, 1‐bromopropane causes toxicity in people and experimental animals. Structurally related haloalkanes are carcinogenic in experimental animals. We are not aware of any organization that has conducted a cancer evaluation of 1‐bromopropane.
Complex Wrinkle Field Evolution

We propose a new approach for representing wrinkles, designed to capture complex and detailed wrinkle behavior on coarse triangle meshes, called Complex Wrinkle Fields. Complex Wrinkle Fields consist of an almost-everywhere-unit complex-valued phase function over the surface; a frequency one-form; and an amplitude scalar, with a soft compatibility condition coupling the frequency and phase. We develop algorithms for interpolating between two such wrinkle fields, for visualizing them as displacements of a Loop-subdivided refinement of the base mesh, and for making smooth local edits to the wrinkle amplitude, frequency, and/or orientation. These algorithms make it possible, for the first time, to create and edit animations of wrinkles on triangle meshes that are smooth in space, evolve smoothly through time, include singularities along with their complex interactions, and that represent frequencies far finer than the surface resolution.
Fixed Echo Rejection in Sodar Using Noncoherent Matched Filter Detection and Gaussian Mixture Model–Based Postprocessing

Doppler sodar is a technology used for acoustic-based remote sensing of the lower planetary boundary layer. Sodars are often used to measure wind profiles; however, they suffer from problems caused by noise (both acoustic and electrical) and echoes from fixed objects, which can bias radial velocity estimates. An experimental bistatic sodar was developed with 64 independent channels. The device enables flexible beamforming; beams can be tilted at the same angle irrelevant of frequency, a limitation in most commercial devices. This paper presents an alternative sodar signal-processing algorithm for wind profiling using a multifrequency stepped-chirp pulse. A noncoherent matched filter was used to analyze returned signals. The noncoherent matched filter combines radial velocity estimates from multiple frequencies into a single optimization. To identify and separate sources of backscatter, noise, and fixed echoes, a stochastic pattern-recognition technique, Gaussian mixture modeling, was used to postprocess the noncoherent matched filter data. This method allowed the identification and separation of different stochastic processes. After identification, noise and fixed echo components were removed and a clean wind profile was produced. This technique was compared with traditional spectrum-based radial velocity estimation methods, and an improvement in the rejection of fixed echo components was demonstrated; this is one of the major limitations of sodar performance when located in complex terrain and urban environments.
Deliberative Quality in Wikimedia Projects: Comparing Requests for Comments on Meta, Wikipedia and Wikidata

Requests for Comments (RfCs) provide a central deliberation space in Wikimedia projects. Analyzing the deliberative quality of RfCs discussions is essential because high-quality deliberation can lead to better decision-making.In this extended abstract, we present ongoing work focusing on comparing deliberative quality in Meta , the English Wikipedia and Wikidata .
A model of (cid:143) uff layer erosion and subsequent bed erosion in the presence of the bioturbator, Hydrobia ulvae

Previous studies have shown that the gastropod Hydrobia ulvae destabilizes the top layers of (cid:142) ne-grained sediments. This process is mediated by the formation of a “biogenic” (cid:143) uff layer that includes tracks, faecal pellets and mucus. This (cid:143) uff layer has been shown to be easily resuspended before general bed erosion. In order to examine how (cid:143) uff layer and bed erosion interact, (cid:143) ume experiments were performed with (cid:143) uid sediments of varying water contents. Ten thousand snails were placed and allowed to crawl for 5 h on the sediment surface,and then the resuspendedsediment mass was measuredin responseto step-wise shear stress increases.Two distincterosionphases were observed: (1) initial resuspension of the (cid:143) uff layer and (2) the subsequent bed erosion. Both the bioturbation by snails and sediment water content interacted positively to increase erosion rates duringthe phaseof (cid:143) uff layererosion.The presenceof a (cid:143) uff layerdue to the snail’s activitiesdid not affect rates of subsequent bed erosion. A vertical model (1DV) was developed to simulate the succession in time of the two distinct erosion phases. Within this deterministic model, erosion rates of the (cid:143) uff layer depend on the quantity of sediment that is present in the (cid:143) uff layer. Previous behavioral observations of track formation mechanisms were integrated into model equations to accountfor the snail densityand the water content dependence.The observed bed erosion was fairly well reproduced by considering the variation with depth of the sediment density as measured in the experiments. This model suggests a new approach for assessing the erosion of natural sediments under the in(cid:143) uence of H. ulvae populationdensity,water contentand tidal currents.
Predicting irrelevant functions of proteins based on dimensionality reduction

Proteins are the foundation for many life processes and accurately annotating their biological functions can significantly boost the development of life sciences. Current function prediction models focus on employing the knowledge that proteins perform specific functions (positive examples), but ignore the knowledge that some functions are irrelevant for a protein (negative examples). Recent research indicates that incorporating negative examples can reduce the complexity and improve the accuracy of protein function prediction. In this paper, we propose an approach for predicting irrelevant functions of proteins based on dimensionality reduction (IFDR). Initially, IFDR performs random walks through matrices in a protein-protein interactions (PPI) network, as well as the corresponding protein-function association matrices, in order to explore the underlying relationships between proteins and model the missing functional annotations of proteins. Next, IFDR uses single value decomposition to project these matrices into low-dimensional numerical matrices. Finally, IFDR uses semi-supervised regression to predict negative examples of proteins. Experiments on S. cerevisiae, H. sapiens, and A. thaliana data demonstrate that IFDR can more accurately predict negative examples when compared to related methods. Dimensionality reduction in the network space and label space can both improve the accuracy of negative example prediction.
Measurements and Calculations of Enhanced Side/Back Scattering of Visible Radiation by Black Carbon Aggregates

Aerosol particles have both natural and anthropogenic origins and are ubiquitous in the atmosphere. One particularly important type is carbonaceous aerosol, including a specific subset, often termed ‘elemental carbon’ chemically or ‘black carbon’ (BC) radiatively. Carbonaceous aerosol particles have implications for atmospheric chemistry, human 15 health, and climate both directly and via their ability to act as site of cloud droplet or ice crystal formation. Laboratory experiments and theory are needed to better understand these particles, specifically their radiative impact. We present here laboratory measurements of side/back scattering of visible radiation by analogues of atmospheric BC aggregates obtained using a depolarizing optical particle counter and accompanying theoretical calculations of scattering by compact and fractal theoretical BC aggregates. We show that with random-orientation, the theoretical calculations reproduce the qualitative 20 behavior of the measurements but are unable to reproduce the highest values of the linear depolarization ratio; we are only able to obtain high values of the linear depolarization ratio using fixed orientation. Thus, we suggest that it is possible that models of scattering by BC aggregates that employ the random orientation assumption/option may underpredict the linear depolarization ratio of actual BC aggregates. Both our measurements and our theoretical calculations point to the possibility that bare (uncoated) BC aggregates, as opposed to the aged/coated BC or soot that was investigated in previous studies, can 25 exhibit higher backscattering linear depolarization than previously assumed.
MIROC6 Large Ensemble (MIROC6-LE): experimental design and initial analyses

Abstract. Single model initial-condition large ensembles (LEs) are a useful approach to understand the roles of forced responses and internal variability in historical and future climate change. Here, we produce one of the largest ensembles thus far using the MIROC6 coupled atmosphere–ocean global climate model (MIROC6-LE). The total experimental period of MIROC6-LE is longer than 76 000 years. MIROC6-LE consists of a long preindustrial control run, 50-member historical simulations, 8 single forcing historical experiments with 10 or 50 members, 5 future scenario experiments with 50 members and 3 single forcing future experiments with 50 members. Here, we describe the experimental design. The output data of most of the experiments are freely available to the public. This dataset would be useful to a wide range of research communities. We also demonstrate some examples of initial analyses. Specifically, we confirm that the linear additivity of the forcing-response relationship holds for the 1850–2020 trends of the annual mean values and extreme indices of surface air temperature and precipitation by analyzing historical fully forced runs and the sum of single forced historical runs. To isolate historical anthropogenic signals of annual mean and extreme temperature for 2000–2020 relative to 1850–1900, ensemble sizes of 4 and 15, respectively, are sufficient in most of the world. Historical anthropogenic signals of annual mean and extreme precipitation are significant with the 50-member ensembles in 76 % and 69 % of the world, respectively. Fourteen members are sufficient to examine differences in changes in annual mean values and extreme indices of temperature and precipitation between the shared socioeconomic pathways (ssp), ssp585 and ssp126, in most of the world. Ensembles larger than 50 members are desirable for investigations of differences in annual mean and extreme precipitation changes between ssp126 and ssp119. Historical and future changes in internal variability, represented by departures from the ensemble mean, are analyzed with a focus on the El Niño/Southern Oscillation (ENSO) and global annual mean temperature and precipitation. An ensemble size of 31 is large enough to detect ENSO intensification from preindustrial conditions to 1951–2000, from 1951–2000 to 2051–2100 in all future experiments, and from low- to high-emission future scenario experiments. The single forcing historical experiments with 27 members can isolate ENSO intensification due to anthropogenic greenhouse gas and aerosol forcings. Future changes in the global mean temperature variability are discernible with 23 members under all future experiments, while 50 members are not sufficient for detecting changes in the global mean precipitation variability in ssp119 and ssp126. We also confirm that these temperature and precipitation variabilities are not precisely analyzed when detrended anomalies from the long-term averages are used due to interannual climate responses to the historical natural forcing, which highlights the importance of large ensembles for assessing internal variability.
This paper is included in the Proceedings of the 17th USENIX Symposium on Operating Systems Design and Implementation.

Data privacy laws like the EU’s GDPR grant users new rights, such as the right to request access to and deletion of their data. Manual compliance with these requests is error-prone and imposes costly burdens especially on smaller organizations, as non-compliance risks steep ﬁnes. K9db is a new, MySQL-compatible database that complies with privacy laws by construction. The key idea is to make the data ownership and sharing semantics explicit in the storage system. This requires K9db to capture and enforce applications’ complex data ownership and sharing semantics, but in exchange simpliﬁes privacy compliance. Using a small set of schema annotations, K9db infers storage organization, generates procedures for data retrieval and deletion, and reports compliance errors if an application risks violating the GDPR. Our K9db prototype successfully expresses the data sharing semantics of real web applications, and guides developers to getting privacy compliance right. K9db also matches or exceeds the performance of existing storage systems, at the cost of a modest increase in state size.
Subproject B2: Conﬁguration and Evaluation

Subproject B2 “Conﬁguration and Evaluation” deals with methods and algorithms for the conﬁguration and evaluation of software services in the OTF Computing scenario. During the three funding periods, various techniques have been developed and implemented for this purpose. Moreover, these techniques have been instantiated and evaluated on case studies from di ﬀ erent domains: image processing, automated machine learning (AutoML), and question answering (QA) systems.
In-sample Actor Critic for Offline Reinforcement Learning

Offline reinforcement learning suffers from out-of-distribution issue and extrapolation error. Most methods penalize the out-of-distribution state-action pairs or regularize the trained policy towards the behavior policy but cannot guarantee to get rid of extrapolation error. We propose In-sample Actor Critic (IAC), which utilizes sampling-importance resampling to execute in-sample policy evaluation. IAC only uses the target Q-values of the actions in the dataset to evaluate the trained policy, thus avoiding extrapolation error. The proposed method performs unbiased policy evaluation and has a lower variance than importance sampling in many cases. Empirical results show that IAC obtains competitive performance compared to the state-of-the-art methods on Gym-MuJoCo locomotion domains and much more challenging AntMaze domains.
Assessing reliability of movement screenings using a markerless motion capture system

Movement screenings are commonly used to detect unfavorable movement patterns. Due to the burdensomeness of markers, markerless motion capture systems have been developed to track three-dimensional motion. This research study investigated the inter- and intra-session reliability of a commercially available markerless motion capture of 39 kinematic variables arising from 10
Chytridiomycota in Tree Bark Chytridiomycota in Tree Bark

Chytridiomycota is a phylum of microscopic aquatic fungi that form motile spores that typically have a single posterior flagellum, thus they require water to disperse (James et al., 2000). Chytridiomycota, collectively called chytrids, have round shapes with structures called rhizoids that absorb nutrients and anchor them to their substrate (Mueller et al., 2004). Chytrids are typically found in aquatic environments and soils since zoospores require water to germinate (James et al., 2000), but they also have been found in a number of unexpected environments. Chytrids are difficult to find because they are microscopic and have time-sensitive life cycles (Mueller et al., 2004). Isolation is difficult because chytrid species require specific nutrients for growth and grow less rapidly than filamentous fungi, yeasts and bacteria. Because chytrids have been found in many habitats and an extensive amount of research on their preferred habitat is lacking, my question was could chytrids be observed and isolated from tree bark samples. In this study bark samples and soil at the base of the trees were collected from red maple ( Acer rubrum ) and amur cork ( Phellodendron amurense ) in Pennsylvania, Sunkhaze wildlife refuge in Milford, Maine, and the University of Maine campus in Orono, Maine. A teaspoon of bark or soil was put in gross cultures to bait chytrids. Every sample contained chytrids, abundantly on spruce pollen grain baits and sparsely on onion skin bait. The Internal transcribed spacer (ITS) regions of the ribosomal gene cassette were amplified from extracted DNA for sequencing and will be used to identify the genera of chytrids collected and isolated from samples. The ITS regions amplify highly variable gene sequences that are used to identify fungi. More research is needed, but these findings support that Chytridiomycota can be found on tree bark.
Priority Based Association Rule Mining to Explore Cloud Services and their Association

Cloud computing has become an essential paradigm in modern IT infrastructure, providing flexible and scalable services to organizations and individuals. With the rapid growth of cloud service offerings, it has become increasingly challenging for users to identify the most suitable services and understand their relationships with other services. Association rule mining techniques have been widely used to discover meaningful patterns and relationships in various domains. In this study, we propose a novel approach called Priority Based Association Rule Mining (PBARM) to explore cloud services and their associations based on user-defined priorities. PBARM leverages user-defined priorities to guide the association rule mining process and extract relevant patterns and relationships. Users can specify their preferences and requirements regarding service characteristics, such as cost, performance, security, and availability. These priorities are then used to assign weights to different attributes and determine the importance of each attribute in the association rule generation process. By considering user-defined priorities, PBARM enables users to focus on the most relevant associations based on their specific needs. To evaluate the effectiveness of PBARM, we conducted experiments using a real-world dataset of cloud services. The results demonstrate that PBARM outperforms traditional association rule mining approaches in terms of relevance and accuracy of the discovered associations. By incorporating user-defined priorities, PBARM provides a more personalized and targeted exploration of cloud services, assisting users in making informed decisions and optimizing their cloud service selections. Furthermore, we developed a user-friendly visualization tool that presents the discovered associations in an intuitive manner, allowing users to interactively explore the relationships between different cloud services. The tool enables users to adjust their priorities dynamically and observe the impact on the generated associations, enhancing the flexibility and usability of the exploration process.
An Analysis of Industrial Relations and Gender Pay Gaps in European Member States 1

This paper proposes an analysis of gender pay gaps (GPGs) and Industrial Relations (IR) in European Member States using data from four waves of the Structure of Earnings Survey (SES) between 2006 and 2018. The links between the GPG and IR have already been studied in the academic literature. However, these analysis usually considered narrower definitions of IR, that focused primarily on the effects of trade union (TU) membership (Card et al, 1996) or certain aspects of wage bargaining (e.g. centralisation, coordination). These IR characteristics impact the GPG because more centralised/coordinated bargaining systems result in more compressed wage distributions (Freeman, 2007) and TU usually seek to impose higher wage floors (Blau and Kahn, 2003) and pursue more egalitarian pay policies (Cardoso and Portugal, 2005). These effects tend to benefit workers at the lower end of the wage distribution, women in particular. 2 The wage compression effects appear to be relatively consensual in the literature, but IR regimes are broader and include dimensions related to the involvement of workers at the firm level (through work councils (WC) or company boards) or to the role given to social dialogue in policymaking (tripartite/bipartite councils/negotiations, see Visser, 2009a). Our focus on IR systems therefore requires a quantitative measure that would encompass all the various aspects of IR and their combinations. A solution is to use the composite index built by Ounnas (2022), which is constructed from 24 variables on four IR dimensions used by Visser (2009b) to construct his typology (i.e. TU strength, wage bargaining, involvement and participation in policy arrangements). This index has the advantage of being available at yearly frequency and for all European countries. It is relevant for our analysis since it assigns high values to IR systems with strong social partners (i.e. high TU and Employer organisation density), some degree of centralisation/coordination of wage bargaining, and workers/unions’ representation at the firm level through work councils (WC).
A Mathematical Approach To Select Best Person For A Job

One of the fuzzy multi-criteria decision making techniques used in this research is the TOPSIS approach, which is commonly used as a selection tool. The many advantages of this strategy led to its selection for this investigation. With only five alternatives, ten people were qualified for an interview. The fuzzy TOPSIS algorithm is used to rank ten candidates and hire the most qualified candidate.