Miracle-dz/UniFAR-FTUs huggingface dataset:
Trägerübergreifende Bedarfsfeststellung – mögliche Ansätze und Perspektiven

To enable self-determination and participation equal with others for persons with disabilities, the social insurance agencies involved in rehabilitation provide benefits for rehabilitation and participation. In order to initiate and perform those benefits individually and purposively, it is necessary to detect and assess a potential need early across social insurance agencies. This requirement was strengthened by the UN Convention on the Rights of Persons with Disabilities. The article outlines the legal background and practical framework conditions for the present assessment duty and refers to examples of existing methods for needs assessment, which in general are still too much aligned to specific benefits. In light of these circumstances, a need for action exists in order to implement legal demands relative to needs assessments across social insurance agencies and to advance approaches already in place.
Modelling opacity and variation in Gran Canarian Spanish apocope

In this paper, we present novel data from Spanish spoken on Gran Canaria which show an interaction of two lenition processes: final consonant deletion and vowel apocope. We show that in certain positions in an utterance, these processes optionally combine in a fed counterfeeding interaction. Furthermore, the variation present in the dialect due to process optionality uncovers a latent opacity pattern, i.e. an additional opaque interaction that is not motivated by any individual input-output mapping, but only by the quantitative aspect of variation. This takes the form of mutual counterfeeding, a rarely reported phenomenon, thus creating a novel test case for theories of opacity. The second part of the paper provides a formal analysis of the opacity-ridden data, taking into account process optionality and variation. The theoretical analysis and learning simulations using the Expectation-Driven Learner demonstrate that a probabilistic variant of Serial Markedness Reduction can capture both fed counterfeeding and latent opacity without recourse to additional mechanisms beyond the original framework, as opposed to analyses in other serial frameworks such as OT-CC. Our analysis shows that opacity with optional processes is a complex problem that has to be specifically addressed with probabilistic frameworks.
Alternative Rule Reasoning: Association Rule Tree Reasoning with a Constraining Rule Ascertained using a Reasoning Framework in 2D Interestingness Area

—Reasoning task is necessary for scientific work. We proposed a method to ascertained association rules from a reasoning framework for rule reasoning tasks. The proposed method does not require defining the values of measures, minimum support, and minimum confidence, which introduce the following reasoning limitations in the conventional method: 1) difficult to define the reasonable values of both measures and 2) difficult to describe the reasoning relation among the determined rules. The reasoning framework is used to derive reasoning relations as sequential relations of the terms related to the domain. A sequential relation can be represented as the relations among a pair of rules between a general rule and its extended rule (i.e., a specific rule). The framework begins from the domain rule, i.e., the first general rule or domain rule acting as the constraining rule (new constraint), and then sequentially determines all the specific rules. The concept behind the reasoning to determine specific rules is that the rule extension should be beneficial (rather than incurring losses). The benefit of rule extension can be represented through the slope of interestingness in a 2D interestingness area, where the X-axis is the support value and the Y-axis is the confidence value. The increasing confidence of the rule extending on the Y-axis should be greater than the decreasing support on the X-axis. The result of the proposed method is an association rule tree branching from the domain rule, i.e., the root node acted as the constraining rule. We discovered this from a breast cancer dataset. The domain is “Class=recurrent-events. ” This tree has only 25 rules with sequential relations of 15 terms related to the domain from 286 records of dataset. Finally, these results are analyzed to verify the usability of the reasonableness.
Machine Learning-Based Traffic Classification in Software-Defined Networking: A Systematic Literature Review, Challenges, and Future Research Directions

—The growing diversification of Internet applications and the continuous evolution of network infrastructure with emerging technologies have complicated network management. Network traffic classification is a key enabler for managing network resources according to the quality of service and security requirements. However, traditional traffic classification methods based on Deep Packet Inspection do not meet the stringent scalability, security, and privacy requirements. The centralized controller of Software-Defined Networking offers a global vision of the network, facilitating traffic analysis and providing direct programming capabilities. Traffic flows can be dynamically adjusted to satisfy the changing network requirements. These characteristics, along with the application of Machine Learning techniques have made it possible to integrate intelligence into networks, optimize them, and better manage and maintain them. In this context, this work aims to provide a Systematic Literature Review on traffic classification in Software-Defined Networking with Machine Learning techniques. Furthermore, we analyze and organize the selected seminal works based on the categorization of traffic classes and the employed Machine Learning techniques to draw meaningful research conclusions. Finally, we identify new challenges and future research directions on this topic.
Multi-objective Optimization Model of Hydrodynamic Sliding Bearing Based on MOPSO with Linear Weighting Method

The machinery manufacturing industry has always been an important pillar of China's economic development. When we solve different problems in mechanical production, people often face the trade-off of having to choose among some desired multiple optimization goals, because many goals cannot often be optimized at the same time, or even conflict with each other. To improve the comprehensive performance of hydrodynamic sliding bearing, the improved multi-objective model is applied to this problem to obtain more reasonable parameter design. We use MOPSO with linear weighting method to solve our proposed model. The results of a numerical example show that our model and algorithm are feasible and more effective than the traditional MOPSO by more reasonable parameter design.
Inside Residential IP Proxies: Lessons Learned from Large Measurement Campaigns

Residential IP Proxy (RESIP) providers represent a growing threat when used for web scraping and other malicious activities. RESIPs enable their customers to hide behind a vast network of residential IP addresses to perpetrate their actions. This helps the customers to evade detection. Thanks to two new large datasets of RESIP connections, we reveal new insights into RESIP inner functioning and modus operandi. We present the similarities and differences of the ecosystems associated with four RESIP providers (geographic distribution, types, management and amount of machines used). Moreover, we display how two of the providers have striking similarities and we propose a specific detection method to identify them. Furthermore, we show how to build a list of suspicious /24 blocks of IP addresses and use it to mitigate the actions of malicious parties behind RESIPs.
Signature of multi-photon interference in boson sampling experiments

The progressive development of quantum technologies in many areas, ranging from investigation on foundamentals of quantum of mechanics to quantum information and computation, has increased the interest on those problems that can exhibit a quantum advantage. The Boson Sampling problem is a clear example where traditional computers fail in the task of sampling from the distribution of n indistinguishable photons after a propagation in a m-mode optical interferometer. In this context, in the absence of classical algorithms able to simulate efficiently multi-photon interference, the validation of Boson Sampling is still an open problem. Here we investigate a novel approach to Boson Sampling validation based on statistical properties of correlation functions. In particular we discuss its feasibility in actual proof-of-principle experiments. Furthermore we provide an extensive study of the physical resources required to validate experiments, investigating also the role of bosonic bunching in high-dimensional applications. Our investigation confirms the goodness of the validation protocol, paving the way to use this toolbox for the validation of Boson Sampling devices.
Semi-automatic Extraction of Academic Transdisciplinary Phraseology: Expanding a Corpus of Categorized Academic Phraseology Using BERT Machine Learning Models (Short Paper)

The lack of access to academic literacy skills and tools is a serious problem, as it furthers inequality among students. In this paper, we propose a methodology to semi-automatically extend a corpus of academic phraseology, previously manually extracted and categorized, using BERT machine learning models. We begin by describing the constitution of the manually extracted and categorized corpus. Next, we briefly discuss how the BERT machine learning model works. Then, we explore the methodology for the semi-automatic extension of the initial corpus: from the constitution of a new corpus, to the preparation of the documents to be processed by the model, to the manual evaluation of the retrieved sentences. We ran two tests, the results of which we report in this paper.
Testing the Effect of Information on Discerning the Veracity of News in Real Time

Despite broad adoption of digital media literacy interventions that provide online users with more information when consuming news, relatively little is known about the effect of this additional information on the discernment of news veracity in real time. Gaining a comprehensive understanding of how information impacts discernment of news veracity has been hindered by challenges of external and ecological validity. Using a series of pre-registered experiments, we measure this effect in real time. Access to the full article relative to solely the headline/lede and access to source information improves an individual's ability to correctly discern the veracity of news. We also find that encouraging individuals to search online increases belief in both false/misleading and true news. Taken together, we provide a generalizable method for measuring the effect of information on news discernment, as well as crucial evidence for practitioners developing strategies for improving the public's digital media literacy.
Doing “Reputation” in the Indian Context: An Employee Perspective

Corporate reputation has been studied as an aggregate of stakeholder perceptions with some emphasis on distinguishing among the perceptions of different stakeholder groups. This study focuses on the perceptions of employees, a critical group of stakeholders, within the Indian context and examines factors that inform an understanding of reputation from an employee perspective and shares the consequences of the same. Building on existing research conducted in developed countries, the study reveals similarities and dissimilarities with existing reputation conceptualizations. Results reveal three new factors, namely stakeholder connect, customer centricity, and company ethos, which are critical to an understanding of reputation from the perspective of Indian employees. Based on factors and attributes emerging from employee perceptions, the study proposes the Loyalty, Engagement, Emotional Connect, and Commitment model, which highlights the consequences of a good reputation in the Indian context.
Use of solution error models in history matching

Uncertainty in reservoir models can be quantified by generating large numbers of history-matched models, and using those models to forecast ranges of hydrocarbons produced. The need to run large numbers of simulations inevitably drives the engineer to compromises in either the physics represented in the reservoir model, or in the resolution of the simulations run. These compromises will often introduce biases in the simulations, and the unknown reservoir parameters are estimated using the biased simulations, which can lead to biases in the parameter estimates. Solution error models can be used to correct for the effects of the biases. Solution error models work by building a statistical model for the differences between fine and coarse simulations (or between full physics and reduced physics simulations) using data from simulations at a limited number of locations in parameter space. The statistical model then produces estimates of the error elsewhere in parameter space; these estimates are used to correct the effects of the coarse model biases. In this work, we apply a solution error model to material balance calculations. Material balance is frequently used in reservoir engineering to estimate the initial oil in place. However such models are very simple, treating the reservoir as a tank and allowing instantaneous equilibration of fluids within the tank. The results of material balance simulations will therefore not be consistent with multi-cell reservoir simulations. We use a model based on Teal South Reservoir in the Gulf of Mexico to demonstrate how an error model can correct a material balance model to the accuracy of a reservoir simulation.
3d $\mathcal{N}=4$ mirror symmetry with 1-form symmetry

The study of 3d mirror symmetry has greatly enhanced our understanding of various aspects of 3d \mathcal{N}=4𝒩=4 theories. In this paper, starting with known mirror pairs of 3d \mathcal{N}=4𝒩=4 quiver gauge theories and gauging discrete subgroups of the flavour or topological symmetry, we construct new mirror pairs with non-trivial 1-form symmetry. By providing explicit quiver descriptions of these theories, we thoroughly specify their symmetries (0-form, 1-form, and 2-group) and the mirror maps between them.
Solving a Safety Game on the Unfolding of Safe Petri Nets

We consider a two-player game on 1-safe Petri nets, in which each player controls a subset of transitions. The players are called ‘user’ and ‘environment’; we assume that the user must guarantee progress on its transitions, and has a safety goal on the system. A play of this game is a run in the unfolding of the net; this is a partial order structure describing all the possible executions of the net. In general, we define a strategy for the user as a map from equivalence classes of markings to subsets of transitions owned by the user. We propose an algorithm to check whether the user has a winning strategy on a finite prefix of the unfolding.
Model order reduction on stationary and dynamical isothermal Newtonian EHD contacts

We are introducing a method to decrease the calculation time of EHD contacts. The method is based on model order reduction (MOR) techniques [1] and will be applied to a stationary and dynamical isothermal Newtonian EHD contact. The contact problem is arranged as one full system of equations [2] - including Reynolds equation with cavitation condition, elasticity equation and force balance -- and solved directly. The full system is solved iteratively by a Newton method with an active set procedure accounting for the unilateral constraints related to the chosen cavitation model. The reduction procedure is executed not only on the linear part representing the elasticity equation of the EHD contact problem [3] but also on the strongly nonlinear and parametric part given by the Reynolds equation. To cope with the cavitation condition within the reduced system, the cavitational area is separated from the computational area and the boundary between those two areas is adapted iteratively. Furthermore the costs of constructing the reduced system are cut by approximating the reduced system function and its J acobian using only a few distinguished nodes We will investigate accuracy and eﬂiciency of the partially reduced system (only linear part), the fully reduced system and the fully reduced system with system approximation (SA) compared to the full system.
Lifting the Heston model

How to reconcile the classical Heston model with its rough counterpart? We introduce a lifted version of the Heston model with n multi-factors, sharing the same Brownian motion but mean reverting at different speeds. Our model nests as extreme cases the classical Heston model (when n=1), and the rough Heston model (when n goes to infinity). We show that the lifted model enjoys the best of both worlds: Markovianity, satisfactory fits of implied volatility smiles for short maturities with very few parameters, and consistency with the statistical roughness of the realized volatility time series. Furthermore, our approach speeds up the calibration time and opens the door to time-efficient simulation schemes.
Diversity of bioprotective microbial organisms in Upper Region of Assam and its efficacy against Meloidogyne graminicola

Meloidogyne graminicola has a well-established negative impact on rice yield in transplanted and direct-seeded rice, resulting in yield losses of up to 20 to 90 percent. Studies were undertaken to isolate potential native strains of bio-control agents to manage the devastating Rice Root Knot Nematode (M. graminicola). Eighteen bacterial strains and eleven fungal strains were isolated from the rhizosphere of crops like rice, okra, ash gourd, chili, beans and cucumber, enveloping diverse soil types from the Upper Brahmaputra Valley region of Assam. Six bacterial strains were gram-positive according to morphological results, while twelve others stained negatively. Fifteen bacteria were rod-shaped, two were coccus and one was diplococcus, and all the bacterial isolates showed signs of movement. All the bacterial strains exhibited positivity for gelatin hydrolysis and catalase test. Seven bacteria showed positive, while eleven showed negative reactions to possess the ability to deduce carbon and energy from citrate. The study of the in vitro efficacy of the twenty-nine bacterial and fungal isolates tested against second-stage juveniles (J2) of Meloidogyne graminicola revealed that all the bacterial and fungal isolates potentially inhibited the test organism and caused significant mortality over sterile water treatment. The promising bacterial and fungal isolates that exhibited mortality above 50% were identified as BSH8, BTS4, BTS5, BJA15, FJB 11 and FSH5. The strain BSH8 exhibited the best result of mortality, with 80.79% mortality against J2 of M. graminicola. The strain BTS4 and BTS5 expressed mortality of 71.29% and 68.75% under in-vitro conditions and were significant. The effective and promising bioagents were identified using the 16 S rRNA sequencing as Bacillis subtilis (BSH8), Bacillus velezensis (BTS4), Alcaligenes faecalis (BTS5), Rhizobium pusense (BJA15), Talaromyces allahabadensis (FSH5) and Trichoderma asperellum (FJB11). These results indicated the microorganism’s potential against M. graminicola and its potential for successful biological implementation. Further, the native strains could be tested against various nematode pests of rice in field conditions. Its compatibility with various pesticides and the implication of the potential strains in integrated pest management can be assessed.
Two-Piece location-scale distributions based on scale mixtures of normal family

ABSTRACT In this work, we study the maximum likelihood (ML) estimation problem for the parameters of the two-piece (TP) distribution based on the scale mixtures of normal (SMN) distributions. This is a family of skewed distributions that also includes the scales mixtures of normal class, and is flexible enough for modeling symmetric and asymmetric data. The ML estimates of the proposed model parameters are obtained via an expectation-maximization (EM)-type algorithm.
On replica-nondiagonal large N saddles in the SYK model

We study the saddle points of the SYK model, formulated in terms of the replica bilocal fields, beyond the replica-diagonal assumption. We find a family of replica-nondiagonal saddle points in the IR limit, where the saddle point equations are separable. We use the Parisi ansatz to find the replicanondiagonal solutions and take the replica limit. The free energy on these solutions is computed, and we find that some of the replica-nondiagonal saddles have lower free energy than the replica-diagonal saddle point.
Work climate from the perspective of nurses: qualitative research

Introduction This study aims to determine the nurses’ view of the work climate. A positive work climate is one of the keys determining factors in improving nurse outcomes and affects patient satisfaction with care. Methods In this qualitative research, a semi-structured interview was used to understand nurses’ perceptions of their work environment. The participants’ responses were recorded and transcribed. Between November and December 2021, 22 nurses participated in the study. Purposive sampling was used to choose nurses for the research, and interviews were performed with these nurses utilizing a semi-structured interview form. The interviews were analyzed using a theme analysis. Results The themes identified in the data centered on four dominant elements that together shaped the prevailing work climate: participation in making decisions, companionship, job satisfaction, and changes they expect. Conclusion It is necessary to implement meetings at the level of departments and hospitals, where employees will receive support from the authorities and learn how they can improve the working climate. Implications for nursing management Research findings on the working climate can help hospital managers makers design interventions to create a good working environment for nurses.
Selection and Optimization of a Bioink Based on PANC-1- Plasma/Alginate/Methylcellulose for Pancreatic Tumour Modelling

3D bioprinting involves using bioinks that combine biological and synthetic materials. The selection of the most appropriate cell-material combination for a specific application is complex, and there is a lack of consensus on the optimal conditions required. Plasma-loaded alginate and alginate/methylcellulose (Alg/MC) inks were chosen to study their viscoelastic behaviour, degree of recovery, gelation kinetics, and cell survival after printing. Selected inks showed a shear thinning behavior from shear rates as low as 0.2 s−1, and the ink composed of 3% w/v SA and 9% w/v MC was the only one showing a successful stacking and 96% recovery capacity. A 0.5 × 106 PANC-1 cell-laden bioink was extruded with an Inkredible 3D printer (Cellink) through a D = 410 μm tip conical nozzle into 6-well culture plates. Cylindrical constructs were printed and crosslinked with CaCl2. Bioinks suffered a 1.845 Pa maximum pressure at the tip that was not deleterious for cellular viability. Cell aggregates can be appreciated for the cut total length observed in confocal microscopy, indicating a good proliferation rate at different heights of the construct, and suggesting the viability of the selected bioink PANC-1/P-Alg3/MC9 for building up three-dimensional bioprinted pancreatic tumor constructs.