Miracle-dz/UniFAR-FTUs huggingface dataset:
Navigating the manifold of skin conductance response quantification approaches

Scientific work rests fundamentally upon data, their measurement, processing, analysis, illustration and interpretation. Raw data have to be processed to be ready for statistical analyses and interpretation. While these processing pipelines can be well defined and standardized, they are often characterized by substantial heterogeneity. Here, we present results from a systematic literature search on the different SCR response quantification approaches used in the literature by using fear conditioning research as a case example. Next, we applied seven of the identified approaches (trough-to-peak scoring, script-based baseline-correction, Ledalab as well as four different models implemented in the software PsPM) to two fear conditioning datasets differing in key procedural specifications (i.e., CS duration, reinforcement rate, number of trials). This can be viewed as a set of robustness analyses (i.e., same data subjected to different methods) aiming to investigate if and to what extent these methods yield comparable results. To our knowledge, no formal framework for the evaluation of robustness analyses exists to date, but we may borrow some criteria from a framework suggested for the evaluation of ‘replicability’ in general. Our results from seven different SCR response quantification approaches applied to two datasets suggest that there may be no single approach that consistently yields larger effect sizes across both datasets. Yet, at least some of the approaches employed show consistent effect sizes within each dataset indicating comparability. Finally, we highlight substantial heterogeneity also within most quantification approaches and discuss implications and potential remedies.
Topology-Enhanced Nonreciprocal Scattering and Photon Absorption in a Waveguide

Topological matter and topological optics have been studied in many systems, with promising applications in materials science and photonics technology. These advances motivate the study of the interaction between topological matter and light, as well as topological protection in light-matter interactions. In this work, we study a waveguide-interfaced topological atom array. The light-matter interaction is nontrivially modified by topology, yielding optical phenomena. We find topology-enhanced photon absorption from the waveguide for a large Purcell factor, i.e., $\mathrm{\ensuremath{\Gamma}}/{\mathrm{\ensuremath{\Gamma}}}_{0}\ensuremath{\gg}1$, where $\mathrm{\ensuremath{\Gamma}}$ and ${\mathrm{\ensuremath{\Gamma}}}_{0}$ are the atomic decays to the waveguide and environment, respectively. To understand this unconventional photon absorption, we propose a multichannel scattering approach and study the interaction spectra for edge- and bulk-state channels. We find that, by breaking inversion and time-reversal symmetries, optical anisotropy is enabled for the reflection process, but the transmission is isotropic. Through a perturbation analysis of the edge-state channel, we show that the anisotropy in the reflection process originates from the waveguide-mediated non-Hermitian interaction. However, the inversion symmetry in the non-Hermitian interaction makes the transmission isotropic. At a topology-protected atomic spacing, the subradiant edge state exhibits huge anisotropy. Because of the interplay between edge- and bulk-state channels, a large topological bandgap enhances nonreciprocal reflection of photons in the waveguide for weakly broken time-reversal symmetry, i.e., ${\mathrm{\ensuremath{\Gamma}}}_{0}/\mathrm{\ensuremath{\Gamma}}\ensuremath{\ll}1$, producing complete photon absorption. We show that our proposal can be implemented in superconducting quantum circuits. The topology-enhanced photon absorption is useful for quantum detection. This work shows the potential to manipulate light with topological quantum matter.
Polyallylamine-Functionalized Platinum Tripods: Enhancement of Hydrogen Evolution Reaction by Proton Carriers

Tailoring the size, controlling the morphology, and designing the metal–organic interface are three promising strategies to improve the catalytic performance of monometallic noble-metal nanocrystals. In the “hydrogen economy” society, water electrolysis is viewed as one of the most promising technologies for hydrogen production. The design and synthesis of highly active and durable electrocatalysts for the hydrogen evolution reaction (HER) is vitally important for the development of the hydrogen economy. In this work, we successfully synthesized polyallylamine (PAA)-functionalized Pt tripods (Pttripods@PAA) with ultrathin and ultralong branches through a facile chemical reduction method in an aqueous solution of PAA. The morphology, structure, and composition of Pttripods@PAA were fully investigated by various physical techniques. The characterization results reveal that ultrathin and ultralong branches of Pttripods@PAA have a concave structure with high-index facets and that PAA strongly binds on the Pt .
Fracture Analysis of Vacancy Defected Nitrogen Doped Graphene Sheets Via MD Simulations

The novel hexagonal monolayer sheet of carbon atoms, graphene, has attracted great attention due to their exceptional electrical and mechanical properties. Their phenomenally high strength and elastic strain, nevertheless, can be altered by structural defects due to stress concentration. In this paper, the fracture behaviour of graphene sheets and nitrogen doped graphene sheets with vacancies were investigated using molecular dynamics (MD) simulations at the different temperatures of 300K, 500K, and 900K. The results reveal a significant strength loss caused by both the defects and vacancies and doped nitrogen in graphene. The deformation process of graphene at various strain rate levels, with regard to the failure behaviour, is discussed. The validity of the proposed MD simulations is verified by comparing the simulation results with the available predictions from the quantized fracture mechanics.
Is low-rate distributed denial of service a great threat to the Internet?

Low ‐ rate Distributed Denial of Service (LDDoS) attacks, in which the attackers send packets to a victim at a sufficiently low rate to avoid being detected, are considered to be a subtype of DDoS attacks and a potential threat to Internet security. However, an over-whelming attack paradigm on the Internet has rarely been reported due to the harsh requirements for launching LDDoS attacks; therefore, most existing LDDoS attacks are constructed and evaluated through theoretical deduction and/or simulation tests. In this backdrop, the authors aim to figure out what the conditions for launching a successful LDDoS attack are, and how harmful an attack could be. They first analyse the characteristics of LDDoS attacks, and derive the conditions and parameters for initiating LDDoS attacks using a queuing model. Based on the analysis results, an LDDoS algo-rithm is presented. Then, an LDDoS validation prototype is built on a Network Function Virtualization network to validate the derived parameters and conditions. Finally, a series of experiments are conducted on the testbed, and the results show that a successful LDDoS attack could be achieved based on the derived algorithm; however, its attack effect only lasts for a short time compared with its DDoS counterparts.
Development of Innovation Economy - Activity of Local Government in Poland

: Purpose: The paper aimed to check the activities of local governments contributing to the development of the innovation economy in Poland as well as to find the answer to the questions if local governments both support innovations, as well as implement innovations themselves. Moreover, the purpose of the paper was to find out if activities of local governments depend on their type (rural, urban, urban-rural) or not? Approach/Methodology/Design: In order to achieve that the method of desk research, quantitative and qualitative research were used. The first part of the research was based on a literature review and the second concerned the development of the survey questionnaire based on the literature review. The questionnaire survey was developed and the whole population (2479) of local governments in Poland, was investigated, in early - using the CAWI method. Findings: We have got the answers from 453 local governments. The conducted analysis showed what kind of innovation is undertaken by Polish local governments frequently, we also find out what kind of activities they undertake to increase the innovation economy. Practical Implications: LGUs should continue implementing the innovations resulting from ICT infrastructure and e-government at local level development. Both the world trends as well as last pandemic time confirmed the need of boosting innovations in this area. Secondly, the LG authorities should cooperate with business actors, coming from the other public sector, academia, and civil society. Originality/Value: The research has enabled to develop a conceptual understanding of the relationship between local government and innovative activities.
Metabolic response to point mutations reveals principles of modulation of in vivo enzyme activity and phenotype

The relationship between sequence variation and phenotype is poorly understood. This is largely due to its complexity, as mutations are pleiotropic and affect several layers of cellular hierarchy, from molecular properties to systems level to the phenotype. Though mapping of phenotype to molecular, cellular and certain systems level properties has been elucidated in some systems, a precise mechanistic understanding of how metabolic perturbations arising out of mutations affect phenotype is lacking. Here we use metabolomic analysis to elucidate the molecular mechanism underlying the filamentous phenotype of E. coli strains that carry destabilizing mutations in the Dihydrofolate Reductase (DHFR). We find that partial loss of DHFR activity causes SOS response indicative of DNA damage and cell filamentation. This phenotype is triggered by an imbalance in deoxy nucleotide levels, most prominently a disproportionate drop in the intracellular dTTP. However, dTTP levels could not be explained by drop in dTMP based on the Michaelis‐Menten like in vitro activity curve of Thymidylate Kinase (Tmk), an enzyme downstream of DHFR that phosphorylates dTMP to dTDP. Instead, we show that a highly cooperative (Hill coefficient 2.5) in vivo activity of Tmk is the cause of suboptimal dTTP levels. dTMP supplementation in the media rescues filamentation and restores in vivo Tmk kinetics to almost perfect Michaelis‐Menten. The cooperative enzyme activity is best explained by the fractal nature of Tmk activity in vivo due to diffusion‐limitation of substrate dTMP, possibly due to substrate channeling and metabolon formation. Overall, this study highlights the important role of cellular environment in sculpting enzyme kinetics. It also demonstrates the use of a systems level property of the cell – metabolome – as a stepping‐stone to illustrate precise biophysical and biochemical mechanisms to bridge the multi‐scale genotype‐phenotype relationship.
A Witch’s Brew of Grievances: The Potential Effects of COVID-19 on Radicalization to Violent Extremism

Abstract Historically, pandemics had inevitably produced demonization and scapegoating, and the COVID-19 pandemic has been no exception. Some individuals and groups have attempted to weaponize and exploit the pandemic, to use it as a means of spreading their extremist ideologies and to radicalize others to their causes. Segmented regression analyses of seven online extremist forums revealed that posting behavior on violent right-wing extremist and incel forums increased significantly following the declaration of the pandemic. The same was not true of left-wing or jihadist forums. These unequal effects likely reflect the particular grievance-based and online nature of right-wing and incel extremism.
Orthogonal tucker decomposition using factor priors for 2D+3D facial expression recognition

In this article, an effective approach is proposed to recognise the 2D + 3D facial expression automatically based on orthogonal Tucker decomposition using factor priors (OTDFPFER). As a powerful technique, Tucker decomposition on the basis of the low rank approximation is often used to extract the useful information from the constructed 4D tensor composed of 3D face scans and 2D images aiming to maintain correlations and their structural information. Finding a set of projected factor matrices is our ultimate goal. During the 4D tensor modelling process, high similarities among samples will emerge because of the information missed partially. Based on the tensor orthogonal Tucker decomposition, the involved core tensor with the structured sparsity, and a graph regularisation term via the graph Laplacian matrix together with the fourth factor matrix are employed for better characterisation of the generated similarities and for keeping the consistency of low dimensional space. To recover the missing information, a framework for tensor completion (TC) will be embedded naturally. Finally, an alternating direction method coupled with the majorisation ‐ minimisation scheme is designed to solve the resulting tensor completion problem. The numerical experiments are conducted on the Bosphorus and the BU ‐ 3DFE databases
Land in transition: from social reproduction of labour power to social reproduction of power

ABSTRACT Ifi Amadiume's seminal work, Male Daughters, Female Husbands developed significant insights into the relationship between gender, wealth and power, and anticipated the centrality of gendered labour processes in the survival of the family/household by highlighting the articulation between reproductive labour and the productive economy. In this epoch when various postcolonial states are grappling anew with land and agrarian questions, Amadiume's detailed study of the decommodification of land is especially salient for feminist inquiry as she has already drawn attention to the ways in which land functions generationally in the reproduction of authority, ritual, governance, kinship and power. This paper proposes a similar move beyond the present discourses which emphasise women's roles in the social reproduction of labour power, asking how a critical reading of Amadiume might help us understand the significance of social reproduction in relation to land as a contemporary realm of feminist power and struggles.
Students’ and Instructors’ Understandings, Attitudes and Beliefs about Educational Theories: Results of a Mixed-Methods Study

(1) Background: Educational theories are a constitutive element of educational studies. Despite their theoretical relevance, little is still known about students’ and instructors’ understandings of educational theories and their theory-related attitudes and beliefs. (2) Methods: To elucidate these constructs and to test their relevance, we conducted a mixed-methods study with 32 students and 12 instructors of educational studies at a German university. (3) Results: We found that both groups perceived educational theories as rather abstract concepts. Students reported rather negative attitudes and naive beliefs. For both groups, we found that attitudes and beliefs were strongly tied to motivational and affective aspects when dealing with educational theories, which stresses their relevance for educational studies. (4) Conclusions: We suggest a systematic theoretical clarification of the term educational theories. Furthermore, consideration of students’ and instructors’ theory-related attitudes and beliefs can give rise to meaningful practical implications (e.g., through self-reflection).
The Effect of Tourism Accessibility Perception Towards Tourists Visiting Intention to Toba Lake in Samosir District

This study aims to see the effect of perceptions received by tourists visiting intention to Toba Lake, Samosir Regency. A quantitative approach method was used by using statistical data in multiple regression analysis. The population was domestic tourists and the sample was 325 respondents who were obtained using random sampling techniques. The results were divided into (1) a significant effect and positive destination accessibility and simultaneously on the intention in tourist visits 2) the ability of the independent variables in explaining the related variables was 53.8% the remaining 46.2% from other variables not discussed in this study 3) the influence of accessibility variable on tourists' visiting intention is strong. From these results it can be concluded that accessibility according to the Apollo concept needs to be improved by the manager of tourist destinations at Toba Lake because the role of accessibility affects the intention to visit tourists to Toba Lake.
Using process data to generate an optimal control policy via apprenticeship and reinforcement learning

Reinforcement learning (RL) is a data-driven approach to synthesizing an optimal con-trol policy. A barrier to wide implementation of RL-based controllers is its data-hungry nature during online training and its inability to extract useful information from human operator and historical process operation data. Here, we present a two-step framework to resolve this challenge. First, we employ apprenticeship learning via inverse RL to analyze historical process data for synchronous identification of a reward function and parameterization of the control policy. This is conducted offline. Second, the parameterization is improved online efficiently under the ongoing process via RL within only a few iterations. Significant advantages of this framework include to allow for the hot-start of RL algorithms for process optimal control, and robust abstraction of existing controllers and control knowledge from data. The framework is demonstrated on three case studies, showing its potential for chemical process control.
Is metabolic syndrome associated with high tumor grade and stage of bladder cancer: a systematic review and meta-analysis

Background The aim of our study was to elaborate the association between metabolic syndrome (MS) and the tumor stage and grade of bladder cancer (BC). Methods A systematic review and pooled analysis on PubMed, the Cochrane Library, Embase, Web of Science, CNKI, WANFANG and VIP from databases inception to July 24, 2020 was conducted by two independent authors. Relative risk (RR) was used as pooled effect estimates. The data analysis was accomplished by STATA 14.2. Results Three English and four Chinese articles were included in the final analysis. A pooled analysis of six studies showed that patients in MS group were at a 1.94-fold risk of high-stage BC when compared to their counterparts (RR: 1.94; 95% CI: 1.59–2.37), and the difference was statistically significant. For the components of MS, except for hypertension, patients with obesity (RR: 1.61; 95% CI: 1.33–1.95), hyperglycemia (RR: 2.20; 95% CI: 1.49–3.26) and low high-density lipoprotein cholesterol (HDL) (RR: 1.98; 95% CI: 1.51–2.58) had significantly higher risks of high-stage BC than the control groups. A pooled analysis of six studies indicated that MS can contribute substantially to the vulnerability of high-grade BC with significant difference (RR: 1.50; 95% CI: 1.37–1.65). Furthermore, patients with obesity (RR: 1.41; 95% CI: 1.18–1.69), hyperglycemia (RR: 1.42; 95% CI: 1.30–1.56), hypertension (RR: 1.13; 95% CI: 1.03–1.24), low HDL (RR: 1.29; 95% CI: 1.14–1.46) and high triglyceride (TG) (RR: 1.28; 95% CI: 1.11–1.46) were at a higher risk of high-grade BC than their counterparts. Conclusions This meta-analysis revealed that MS and its components might be associated with high BC stage and grade.
Simulation of Transport through OmpF and OmpC Channels

The outer membrane porins F and C (OmpF and OmpC) are major pores in the cell membrane of the Gram-negative bacterium Escherichia coli. They are considered the main pathways for ions and molecules through the membrane. Using the crystal structures, it is possible to study OmpF and OmpC in computer simulations. In this thesis, the ion conductance through these nano pores is simulated in all-atom molecular dynamics. Although the amino acid sequences of both pores are similar, their conductance is diﬀerent. The temperature dependence of the conductance is calculated for diﬀerent salt concentrations. Good agreement is seen in the comparison between simulations and experiments. The advantage of molecular dynamics simulations is that they allow a deeper view on the molecular interaction leading to the macroscopic observation. Ion pathways can be followed, and the interaction of ions with certain residues can be observed. Both pores, OmpF and OmpC, have a charged constricted area in the middle of the pore. The behavior of the pore can be changed by mutating key residues in this constriction zone. The effect of mutations on the transport of ions is investigated and compared to the results obtained from wild type OmpF. Also here, experimental measurements show good agreement with the simulations. Furthermore, porins are the main pathways of antibiotics into the cell. The translocation of antibiotics through membrane is not yet understood in all details. During translocation, a blocking of pores through antibiotics is observed. Here, blocking of porins by the beta lactam antibiotic ampicillin is simulated, as well as, translocation of ampicillin through OmpF.
Banking news-events representation and classification with a novel hybrid model using DistilBERT and rule-based features

This paper discusses a novel hybrid approach to text classification that integrates a machine learning algorithm along with DistilBERT, a pre-trained deep learning framework for natural language processing, offers a base model fine-tuned on Indian Banking News-Events with a rule-based method that is used by filtering false positives and dealing with false negatives to enhance the results given by the previous classifier. The major benefit is that by incorporating unique rules for certain chaotic or overlapping categories that have not been effectively trained, the system can be quickly fine-tuned. This research also compares the effectiveness of state-of-art deep contextual language representation DistilBERT used in our proposed hybrid model with the most preferred context independent language representation TFIDF, on supervised learning of the classification of multiclass Banking News-Events. Both representations are fed into the machine learning classifiers, Logistic Regression, Linear SVC, Decision Tree, and Random Forest. The findings indicate that DistilBERT can better transfer generic domain knowledge to other domains as compared to the baseline TFIDF and results into higher accuracy with Random Forest. The result is further fed into the Rules based method as per our proposed model. And, our proposed hybrid model resulted into improved accuracy.
Estimation of the precision of isosteric heats of sorption determined from the temperature dependence of food isotherms

This work estimates the influence of the experimental error in the determination of food isotherms on the precision of isosteric heats calculated by application of the Clausius-Clapeyron equation. Foods for which precise sorption data are available were analyzed; the resulting uncertainty in calculated heats was important and suggested that alternative techniques should be used when a more quantitative picture of the heat of sorption is desired