Miracle-dz/UniFAR-FTUs huggingface dataset:
THE WHYBURN PROPERTY AND THE CARDINALITY OF TOPOLOGICAL SPACES

The weak Whyburn property is a generalization of the classical sequen- tial property that was studied by many authors. A space X is weakly Whyburn if for every non-closed set A ⊂ X there is a subset B ⊂ A such that B \A is a single- ton. We prove that every countably compact Urysohn space of cardinality smaller than the continuum is weakly Whyburn and show that, consistently, the Urysohn assumption is essential. We simultaneously solve a question of Pelant, Tkachenko, Tkachuk and Wilson and one of Bella, Costantini and ourselves by constructing a Lindelof P-space of cardinality ! 2 that is not weakly Whyburn. We give conditions for a weak Whyburn space to be pseudoradial and construct a countably compact weakly Whyburn non-pseudoradial regular space, which solves a question asked by Bella in private communication.
Analysis on the Control Strategies of Hip Exoskeletons and Exosuits

Lower limb exoskeleton has been proven to be effective in gait training and locomotion assistance. Specifically, control strategies of exoskeletons play the most important role in safe and effective interaction between the user, the exoskeleton, and the environment. In this paper, an analysis on the control strategies of hip exoskeletons and exosuits is performed. The controls are divided into three levels: high, medium, and low. The definition of high-level control as well as the corresponding control methods are listed and the principle of each is explained. Then, the mid-level control section is divided between detection and action layer and each control that belongs to one of the two categories is analyzed. The definition of low-level control and its control methods are then explained. At last, according to the results of various studies, the advantages and potential disadvantages of each method are put forward. The purpose of this paper is to provide reference and guidance for future researchers who hope to develop new controls or improve existing control strategies for hip exoskeletons and exosuits.
Customer Journey Value: A Conceptual Framework

Though firms are making substantial investments in the customer journey (CJ), the return on these investments remains tenuous, yielding a critical need for enhanced CJ-related accountability. Addressing this gap, we develop the concept of ‘customer journey value’ (CJV), defined as the perceived value of a customer’s journey to the customer and the firm, which facilitates the development of accountability in this regard. We also develop a social exchange theory-informed framework of CJV, which proposes customer- and firm-based customer engagement value (CEV) as core CJV antecedents. In turn, CJV is predicted to yield the customer-based consequences of attitudinal and behavioural brand loyalty and the firm-based consequences of enhanced customer lifetime value, as formalized in a set of propositions based on the framework. We conclude by outlining pertinent implications that arise from our analyses.
Multi-Responsive Molecular Encapsulation and Release Based on Hydrogen-Bonded Azo-Macrocycle

Research on stimuli-responsive host–guest systems is at the cutting edge of supramolecular chemistry, owing to their numerous potential applications such as catalysis, molecular machines, and drug delivery. Herein, we present a multi-responsive host–guest system comprising azo-macrocycle 1 and 4,4′-bipyridinium salt G1 for pH-, photo-, and cation- responsiveness. Previously, we reported a novel hydrogen-bonded azo-macrocycle 1. The size of this host can be controlled through light-induced E↔Z photo-isomerization of the constituent azo-benzenes. The host is found in this work to be capable of forming stable complexes with bipyridinium/pyridinium salts, and implementing guest capture and release with G1 under light in a controlled manner. The binding and release of the guest in the complexes can also be easily controlled reversibly by using acid and base. Moreover, the cation competition-induced dissociation of the complex 1a2⊃G1 is achieved. These findings are expected to be useful in regulating encapsulation for sophisticated supramolecular systems.
Learning Companions motivierend gestalten

1 Einleitung In einer zunehmend digitalen und sich rasant verändernden Arbeitswelt, wird lebenslanges Lernen immer wichtiger für den beruflichen Erfolg (OECD, 2021). Technologische Entwicklungen und der Trend zum digitalen Lernen und Arbeiten, schaffen neue Möglichkeiten für die berufsbegleitende Weiterbildung. Jedoch verschwimmen Freizeitund Arbeitswelt dadurch zunehmend, was oftmals in Stress, Erschöpfung und fehlender Motivation zum Lernen mündet (Limarutti, Flaschberger, & Mir, 2021; Nickel, Püttmann, & Schulz, 2018) – ein Umstand der durch die Verlagerung zugunsten der digitalen Lehre mit erhöhter Selbstorganisation noch weiter zugenommen hat (Winde, Wernder, Gumbmann, & Hieronimus, 2020) und sich in hohen Abbruchquoten beim e-Learning widerspiegelt (Nickel, Püttmann, & Schulz, 2018). Learning Companions (LCs), also digitale, natürlich-sprachige Agenten (Chatbots oder sprachbasierte Assistenten), die eine freundschaftsähnliche Beziehung zu ihrem menschlichen Nutzer aufbauen, stellen einen innovativen Lösungsansatz dar, um Menschen vielfältig, individualisiert sowie zeitund ortsunabhängig beim Lernen zu unterstützen (Khosrawi-Rad et al., 2022). Da eine hohe Motivation einen positiven Effekt auf den Lernerfolg und dessen Nachhaltigkeit hat (Hawlitschek & Merkt, 2018), jedoch gleichzeitig, insbesondere im digitalen Raum ein großes Problemfeld darstellt (Limarutti et al., 2021), forcieren wir den Einsatz eines LCs in seiner Rolle als Motivator.
DDoS attacks and machine‐learning‐based detection methods: A survey and taxonomy

Distributed denial of service (DDoS) attacks represent a significant cybersecurity challenge, posing a critical risk to computer networks. Developing an effective defense mechanism against these attacks is crucial but challenging, given their diverse attack types, network and computing platform heterogeneity, and complex communication protocols. Moreover, the emergence of innovative DDoS attack methods presents a formidable threat to existing countermeasures. Various machine learning techniques have shown promise in detecting DDoS attacks with low false‐positive rates and high detection rates. This survey paper offers a comprehensive taxonomy of machine learning‐based methods for detecting DDoS attacks, reviewing supervised, unsupervised, hybrid approaches, and analyzing the related challenges. Further, we explore relevant datasets, highlighting their strengths and limitations, and propose future research directions to address the current gaps in this domain. This paper aims to provide a profound understanding of DDoS attack detection mechanisms, aiding researchers, and practitioners in developing effective cybersecurity approaches against such attacks. This research is essential because DDoS attacks are diverse and pose a formidable threat to computer networks, and various machine learning techniques have shown promise in detecting them. Its implications include providing insights that can inform the development of robust defense mechanisms against DDoS attacks.
Teaching Metacognitive Reading Strategies To Primary School Students Through Digital Games

Digital platforms have expanded technology-based instruction, providing teachers with a wide range of diverse applications. This study examines the impact of digital games and activities that aim to teach metacognitive reading strategies to primary school students on the attitudes towards reading, as well as on the metacognitive knowledge and skills. Teaching resources have been created in various digital programs such as Power point or Word wall. Digital games and activities aim to develop both metacognitive knowledge (before, during and after reading) and metacognitive skills through strategies such as visualization, self-monitoring and summarization. Tested during speech therapy classes on a number of 30 students with reading difficulties, the digital activities obtained high indicators of effectiveness, both in terms of the attractiveness of the items and the attitude toward reading (measured pre-and post-test with The Elementary Reading Attitude Survey), as well as in terms of metacognitive knowledge and skills during reading (measured pre-and post-test with the Metacomprehension Strategy
Electron-Electron Interactions in Optical Properties of Graphene Quantum Dots

In this thesis, I present a theory of electron-electron interactions in optical properties of graphene and transition metal dichalcogenides (TMDCs), two dimensional nanostructures with a hexagonal lattice. We start our discussion with electron-electron interactions in artificial rings for which the strength of interactions can be varied and exact results can be obtained. The artificial rings are described by the extended Hubbard model and solved using an exact diagonalization method in real and Fourier space of configurations. Exact and analytical results for charged rings are obtained in the limit of very strong interactions. For the quadruple quantum dot ring and the artificial benzene ring, we find that chirality leads to the appearance of a topological phase and an effective gauge field that determines the ground state character with varied interaction strength. For the charged artificial benzene ring, our numerical results show a transition from a degenerate to a non-degenerate ground state with increasing strength of Coulomb interactions. We show that the artificial gauge and the transition in the ground state can be detected as changes in the optical absorption spectrum. In the second part of the thesis, the electronic and optical properties of colloidal graphene quantum dots (CGQD) consisting of many benzene rings are determined. The CGQDs are described by the combination of tight binding, mean field Hartree Fock (HF) and Configuration Interaction methods. The single particle properties are described through the tight binding method based on the pz carbon orbitals. Screened Coulomb interactions between electrons, including direct, exchange, and scattering matrix elements, are calculated using Slater pz orbitals. HF ground states corresponding to semiconductor, Mott-insulator, and spin-polarized phases are obtained as a function of the strength of the screened interaction versus the tunnelling matrix element. The many-body ground and excited states in the semiconducting phase are constructed as a linear combination of a finite number of electron-hole pair excitations from the HF ground state (GS). The Hamiltonian is constructed in the subspace of multi-pair HF excitations to obtain the low energy, many body states by exact diagonalization using the Lanczos method. The degeneracy of the valenceand conduction-band edges of 3-fold rotationally sym-
Therapeutic Potential of a Small-Molecule STAT3 Inhibitor in a Mouse Model of Colitis

Simple Summary We used the dextran sodium sulfate (DSS) murine model of colitis, which is widely used in preclinical studies, to determine the contribution of STAT3 to IBD. STAT3 has two isoforms: (STAT3α; which has pro-inflammatory and anti-apoptotic functions, and STAT3β; which attenuates the effects of STAT3α). In the current study, we determined the contribution of STAT3 to IBD across all tissues by examining DSS-induced colitis in mice that express only STAT3α and in mice treated with TTI-101, a direct small-molecule inhibitor of both isoforms of STAT3. We demonstrated that DSS-induced colitis is more severe in mice that express only STAT3α compared to wild-type mice and that administration of TTI-101 completely prevented DSS-induced colitis as well as reversed upregulation of CRC-associated genes. Abstract Background and Aims: Inflammatory bowel disease (IBD) predisposes to colorectal cancer (CRC). In the current studies, we used the dextran sodium sulfate (DSS) murine model of colitis, which is widely used in preclinical studies, to determine the contribution of STAT3 to IBD. STAT3 has two isoforms: (STAT3 α; which has pro-inflammatory and anti-apoptotic functions, and STAT3β; which attenuates the effects of STAT3α). In the current study, we determined the contribution of STAT3 to IBD across all tissues by examining DSS-induced colitis in mice that express only STAT3α and in mice treated with TTI-101, a direct small-molecule inhibitor of both isoforms of STAT3. Methods: We examined mortality, weight loss, rectal bleeding, diarrhea, colon shortening, apoptosis of colonic CD4+ T-cells, and colon infiltration with IL-17-producing cells following 7-day administration of DSS (5%) to transgenic STAT3α knock-in (STAT3β-deficient; ΔβΔβ) mice and wild-type (WT) littermate cage control mice. We also examined the effect of TTI-101 on these endpoints in DSS-induced colitis in WT mice. Results: Each of the clinical manifestations of DSS-induced colitis examined was exacerbated in ΔβΔβ transgenic versus cage-control WT mice. Importantly, TTI-101 treatment of DSS-administered WT mice led to complete attenuation of each of the clinical manifestations and also led to increased apoptosis of colonic CD4+ T cells, reduced colon infiltration with IL-17-producing cells, and down-modulation of colon mRNA levels of STAT3-upregulated genes involved in inflammation, apoptosis resistance, and colorectal cancer metastases. Conclusions: Thus, small-molecule targeting of STAT3 may be of benefit in treating IBD and preventing IBD-associated colorectal cancer.
Multiple Regression and Big Data Analysis for Predictive Emission Monitoring Systems

Predictive Emission Monitoring Systems (PEMS) offer a cost-effective and environmentally friendly alternative to Continuous Emission Monitoring Systems (CEMS) for monitoring pollution from industrial sources. Multiple regression is one of the fundamental statistical techniques to describe the relationship between dependent and independent variables. This model can be effectively used to develop a PEMS, to estimate the amount of pollution emitted by industrial sources, where the fuel composition and other process-related parameters are available. It often makes them sufficient to predict the emission discharge with acceptable accuracy. In cases where PEMS are accepted as an alternative me-thod to CEMS, which use gas analyzers, they can provide cost savings and sub-stantial benefits for ongoing system support and maintenance. The described mathematical concept is based on the matrix algebra representation in multiple regression involving multiple precision arithmetic techniques. Challenging numerical examples for statistical big data analysis, are investigated. Numerical examples illustrate computational accuracy and efficiency of statistical analysis due to increasing the precision level. The programming language C++ is used for mathematical model implementation. The data for research and development, including the dependent fuel and independent NOx emissions data, were obtained from CEMS software installed on a petrochemical plant.
Virus for Women Employees: Exploring the Stereotypical Beliefs of the Leaders about their Female Followers

The never-ending gender discrimination in societies needs multidimensional exploration to understand its causes. Gender stereotyping has remained one of the foremost causes of gender discrimination in the workplace. This study strived to explore the stereotypical thinking and beliefs about women employees in the minds of their office leaders and discusses how these stereotypes play role in management of talent and performance of female employees. With the qualitative approach, this study has used hermeneutic phenomenology as the method of exploration. The data was collected with purposive sampling from managerial leaders, working in private companies whose followers include women employees. Nineteen in-depth interviews were conducted with a question designed from theory, expert and construct validity. The data were analyzed with multi-level coding and thematic analysis. The results revealed that managerial leaders have work-related, family-related and personal stereotypes about their female followers. They generalize that women employees are less ambitious, less professional, over occupied an emotional. They believe that they feel need to micromanage the females as they require more guidance. Those organizations that believe to maintain the diversity in employees should regularly organize training sessions to neutralize the stereotypes in the minds of their managers so that they could not hamper the progression of their female followers. Keywords: Stereotypical Beliefs; Female Followers; Leadership; Organizational Behavior
MUSLIM WOMEN SWITCHING INTENTION TO HALAL COSMETIC: PUSH-PULL-MOORING MODEL APLICATION

This study focuses on the factors that contribute to switching intentions from non-halal cosmetics to halal cosmetics by Muslim women in Indonesia. Using a questionnaire and purposive sampling, we compile data from a total of 236 women who use halal cosmetics and then apply the SEM-PLS for data analysis. The results show that the pull effect significantly affects Muslim women's intention to switch to halal cosmetics and is moderated negatively by switching costs. While the push effect doesn’t significantly affect the intention to switch to halal cosmetics. In addition, halal awareness and switching costs directly affect Muslim women's switching intentions from non-halal to halal cosmetics.
Leadership repertoire and political engagement in a divided city: The case of East Jerusalem

Do the leaders of minority communities in divided cities influence group members’ expressed willingness to engage politically with rival groups? Studies typically link group members’ willingness to engage with rival groups to direct contact between individuals from opposing groups. However, such contact is problematic in divided cities, wherein opportunities to interact are scarce and frowned upon. Focusing on the contested urban space of Jerusalem, we find indications that the diverse nature of community leadership in East Jerusalem can influence Palestinian residents’ attitudes towards political engagement with Israeli authorities via municipal elections. The ‘middlemen’ role can explain community leaders’ influence in divided cities. They facilitate indirect contact between their constituents and the other group’s members or institutions. Our analysis employs original data from a public opinion survey conducted among Palestinian residents of East Jerusalem immediately prior to the Jerusalem 2018 municipal elections. It has ramifications regarding urban governance for other divided cities.
Embedding the Patient-Citizen Perspective into an Operational Framework for the Development and the Introduction of New Technologies in Rehabilitation Care: The Smart&Touch-ID Model

To date, at least 2.41 billion people with Non-Communicable Diseases (NCDs) are in need of rehabilitation. Rehabilitation care through innovative technologies is the ideal candidate to reach all people with NCDs in need. To obtain these innovative solutions available in the public health system calls for a rigorous multidimensional evaluation that, with an articulated approach, is carried out through the Health Technology Assessment (HTA) methodology. In this context, the aim of the present paper is to illustrate how the Smart&TouchID (STID) model addresses the need to incorporate patients’ evaluations into a multidimensional technology assessment framework by presenting a feasibility study of model application with regard to the rehabilitation experiences of people living with NCDs. After sketching out the STID model’s vision and operational process, preliminary evidence on the experiences and attitudes of patients and citizens on rehabilitation care will be described and discussed, showing how they operate, enabling the co-design of technological solutions with a multi-stakeholder approach. Implications for public health are discussed including the view on the STID model as a tool to be integrated into public health governance strategies aimed at tuning the agenda-setting of innovation in rehabilitation care through a participatory methodology.
Towards an efficient approach using graph-based evolutionary algorithm for IoT botnet detection

In recent years, a large number of Internet of Things devices are used in life, many of which are vulnerable to attacks from a security perspective. Botnet malware is one of the main threats to IoT devices. Hence detection of IoT botnet is one of the most important challenge for IoT devices. This paper proposes an IoT botnet detection approach based on PSI graph data combine with evolutionary algorithm-based technique. In recent years, a large number of Internet of Things devices are used in life, many of which are vulnerable to attacks from a security perspective. Botnet malware is one of the main threats to IoT devices. Hence detection of IoT botnets is one of the most important challenges for IoT devices. In the paper, a IoT botnet detection approach based on PSI graph analysis by using the evolutionary algorithmbased technique. It applies bacterial evolution algorithm (BEA) in the training process on PSI graph multi-architecture IoT Botnet data to detect IoT Botnet. The PSI graphs were extracted from executable files and transform into vectors to feed into the classical machine learning classifiers. The result of the classifiers is then combine using soft voting method with BEA. The proposed method has achieved good experimental results (i.e., Accuracy at 95.30%, F1 at 96.15%). The approach also achieves a relatively low false-positive rate at 4.59%.
Risk Factors and Treatments Impacts for the Gene of Two Different Types of Skin Cancer: Survival Analysis

Two distinct types of skin cancer are Cutaneous Melanoma and Melanoma of Uncertain Primary. Their causes may be distinct. Several variables, including genetic mutation, UV exposure, sex, age, and others, will affect the survival months. In this study, the Kaplan-Meier method and the Cox model will be used to compare the two types of skin cancer. For the KM technique, one unique variable will be employed to assess its association with the survival months. Cox model will employ multiple variables to describe the overall association between several variables and the survival months. In conclusion, the difference on sex will have a distinct impact on two different kinds of skin cancer. Genetic expression does not clearly differentiate between them. UV exposure and therapy have a substantial impact on the number of months of survival for Cutaneous Melanoma. The results of the study indicate that additional research and prevention are required. Prevention is almost always more effective than treatment for cancer. For specific patient populations, clinicians should prioritize skin cancer prevention and therapy.
Overexpressing Ribosomal Protein L16D Affects Leaf Development but Confers Pathogen Resistance in Arabidopsis

In plant cells, multiple paralogs from ribosomal protein (RP) families are always synchronously expressed, which is likely contributing to ribosome heterogeneity or functional specialization. However, previous studies have shown that most RP mutants share common phenotypes. Consequently, it is difficult to distinguish whether the phenotypes of the mutants have resulted from the loss of specific genes or a global ribosome deficiency. Here, to investigate the role of a specific RP gene, we employed a gene overexpression strategy. We found that Arabidopsis lines overexpressing RPL16D (L16D-OEs) display short and curled rosette leaves. Microscopic observations reveal that both the cell size and cell arrangement are affected in L16D-OEs. The severity of the defect is positively correlated with RPL16D dosage. By combining transcriptomic and proteomic profiling, we found that overexpressing RPL16D decreases the expression of genes involved in plant growth, but increases the expression of genes involved in immune response. Overall, our results suggest that RPL16D is involved in the balance between plant growth and immune response.