Miracle-dz/UniFAR-FTUs huggingface dataset:
Is There A Right Way to Love? : Mindset in Romantic Relationships

Romantic relationships are a very integral and fascinating aspect of life, and have been the subject of interest for poets, philosophers and psychologists alike since time immemorial. In spite of all of humanity’s efforts to understand romantic relationships, there’s no known formula to lasting love. Yet, efforts to understand love, to comprehend why some loves last and some don’t, continue. New concepts keep entering the arena to explain love, and one such concept that has garnered much interest in recent times is Mindset. Though popularly associated with professional success, Mindset can make a difference in interpersonal relationships too (Dweck, 2006). The present study is an attempt to explore the role of Mindset in perceptions of one’s romantic relationship. In order to generate a holistic understanding, both qualitative and quantitative approaches were undertaken. The sample comprised of 30 people between 18 to 50 years who had been in a romantic relationship sometime in their life, in the past or currently. The participants submitted two sets of dataa narrative enquiry in the form of life stories, visual narrative data etc, and responses to three questionnaires: Adult Rejection Sensitivity Questionnaire (Downey & Feldman, 1996), Relationship Assessment Scale (Hendrick, 1988) and the Implicit Theory of Relationships (destiny vs. growth) Scale (Franiuk, Cohen, &Pomerantz, 2002). The qualitative data underwent Thematic Analysis and the quantitative data were analyzed using inferential statistics. Findings suggested that participants who have a growth mindset derive greater satisfaction from their romantic relationships and are less sensitive to rejection. This study has implications for all stakeholders working with interpersonal relationships.
An adaptive lateral preview driver model

Successful modelling and simulation of driver behaviour is important for the current industrial thrust of computer-based vehicle development. The main contribution of this paper is the development of an adaptive lateral preview human driver model. This driver model template has a few parameters that can be adjusted to simulate steering actions of human drivers with different driving styles. In other words, this model template can be used in the design process of vehicles and active safety systems to assess their performance under average drivers as well as atypical drivers. We assume that the drivers, regardless of their style, have driven the vehicle long enough to establish an accurate internal model of the vehicle. The proposed driver model is developed using the adaptive predictive control (APC) framework. Three key features are included in the APC framework: use of preview information, internal model identification and weight adjustment to simulate different driving styles. The driver uses predicted vehicle information in a future window to determine the optimal steering action. A tunable parameter is defined to assign relative importance of lateral displacement and yaw error in the cost function to be optimized. The model is tuned to fit three representative drivers obtained from driving simulator data taken from 22 human drivers.
Contractor selection in government procurement auctions: a case study

This paper aims to present a combined fuzzy Analytical Hierarchical Process (AHP) and Simple Multi-Attribute Ranking Technique (SMART) approach to deal with the contractor selection problem in government procurement auctions. The proposed approach utilises a set of ten attributes for the evaluation of a contractor. In this approach, the attributes of both the past performance and the present status of the contractor is considered wherein the selection attributes are qualitative and/or quantitative type having inhibiting and/or enabling in nature. A case study of the Rural Development Department of the government of Orissa has been taken up to demonstrate the contractor selection process. [Submitted 9 February 2008; Revised 27 June 2008; Revised 8 August 2008; Accepted 12 August 2008]
Generative Models for Handwritten Digits

- Ordinary deep networks are effective for creating discriminative models, but sometimes a generative model is necessary, particularly if one wishes to construct new data according to a target distribution. Generative adversarial networks have been shown to realize such generative models and to generate realistic, structurally sound images. We implemented a deep convolutional generative adversarial network and applied it to the MNIST dataset. We qualitatively discuss the results and analyze the convergence of the GAN
Decoupling film thickness and interface permeability effects on the mass transfer between microbubbles

Hypothesis The role of interfacial coatings in gas transport dynamics in foam coarsening is often difficult to quantify. The complexity of foam coarsening measurements or gas transport measurements between a bubble and air-water interface requires assumptions about the liquid thin film thickness profile in order to explore the effects of interfacial coatings on gas transport. It should be possible to independently quantify the effects from changes in film thickness and interfacial permeability by using both atomic force microscopy and optical microscopy to obtain time snapshots of this dynamic process. Experiments We measure the mass transfer between the same nitrogen microbubbles pairs in an aqueous solution using two methods simultaneously. First, we quantify the bubble volume changes with time via microscopy and second, we use Atomic Force Microscopy to measure the film thickness and mass transfer resistances using a model for the gas transport. Findings Modelling of the interface deformation, surface forces and mass transfer across the thin film agrees with independent measurements of changes in bubble size. We demonstrate that an anionic surfactant does not provide a barrier to mass transfer, but does enhance mass transfer above the critical micelle concentration. In contrast, a polymer monolayer at the interface does restrict mass transfer.
SATURATED IRON-CORE SUPERCONDUCTING FAULT CURRENT LIMITER AND DVR TRANDIENT ANALYSIS

While other fault current limiters have superior technical performance, the saturated iron-core super conducting fault current limiter outperforms them all by a significant margin. Magnetic structures have been proposed based on the actual structure. The Newton iteration technique and the fundamental magnetization curve were both employed to calculate the current limiting inductance during the simulation. While faulting, the current levels went through major sags and waves. Voltage fluctuations and short circuits are two of the most common challenges in grid functioning. Fault current and voltage fluctuation were reduced by using the SISFCL and the DVR in this project. Modeling these devices using Matlab/Simulink and then comparing the findings to theoretical ones allowed us to create an electromagnetic transient simulation model. These devices' transient behaviour during simulation tests shows that the proposed method is accurate and valid.
An Overview of VLSI Memory Yield Management by Injection of Fault Tolerance

Presents an overview of memory chip yield enhancement techniques by injection of fault tolerance. As memory chips are more prone to defects, the yield of good chips from a silicon wafer governs their production cost. As shown, most fault tolerance techniques assume a relatively large area overhead which results in additional costs in terms of the silicon used as well as the lower number of chips/wafers produced. Proper management of fault tolerance, as by the word redundancy approach, adds an almost negligible area overhead to the chip and leads to considerably higher yields.
Development of textiles to combatcold weather in mountain terrains

Technical textiles is a major area in the field of textiles. One aspect of technical textiles is the use in military applications. This article reviews the one area in the use of textiles in military applications. Operation of Armed Forces personnel in harsh military terrains for extended tenure period necessitates protection from elements and battle hazards. Harsh military terrains exert profound effects on the physical and physiological performance of the soldiers and can impart serious health hazards on inadequately protected soldiers resulting in mission failure and avoidable loss of lives. Harsh military terrains can be Mountain environment characterized by treacherous terrains with extreme cold and hypoxia, Deserts characterized by extreme heat stress, Depths of underwater that can pose life threatening situation in case of a distressed submarine, Aviation hazards (such as deadly G-forces faced by fighter pilots during G-manoeuvres and fire hazards that may result from crash) etc. Clothing being the first layer of protection for the wearer, forms an important protective measure in military operation against combat and environmental hazards. A great deal of research is being carried out by military/defence research laboratories worldwide in collaboration with industries to develop technical textiles incorporating suitable smart material finishes for the alleviation of the dangers associated in the combat terrain.
Self-adaptive Middleware Support for IoT and CPS A Systematic Literature Review

This review classifies and analyzes studies on self-adaptation mechanisms for IoT/CPS. The role of middleware platforms to facilitate such self-adaptation is highlighted. We applied the standard extraction framework to select 62 papers among 4,274 candidate studies. We further analyzed three CPS4EU project’s industrial use-cases based on the review outcomes to propose improvement solutions. Main findings are: i) the adaptation requirement may arise due to changes in system, environment, and their coordination; ii) data-driven proactive adaptation approaches are newly getting more attention; iii) the potential industrial adoption of middleware platforms depends on industry requirements and platforms’ design approaches.
BLACKSMITH: Scalable Rowhammering in the Frequency Domain

We present the new class of non-uniform Rowhammer access patterns that bypass undocumented, proprietary in-DRAM Target Row Refresh (TRR) while operating in a production setting. We show that these patterns trigger bit flips on all 40 DDR4 DRAM devices in our test pool. We make a key observation that all published Rowhammer access patterns always hammer “aggressor” rows uniformly. While uniform accesses maximize the number of aggressor activations, we find that in-DRAM TRR exploits this behavior to catch aggressor rows and refresh neighboring “victims” before they fail. There is no reason, however, to limit Rowhammer attacks to uniform access patterns: smaller technology nodes make underlying DRAM technologies more vulnerable, and significantly fewer accesses are nowadays required to trigger bit flips, making it interesting to investigate less predictable access patterns. The search space for non-uniform access patterns, however, is tremendous. We design experiments to explore this space with respect to the deployed mitigations, highlighting the importance of the order, regularity, and intensity of accessing aggressor rows in non-uniform access patterns. We show how randomizing parameters in the frequency domain captures these aspects and use this insight in the design of Blacksmith, a scalable Rowhammer fuzzer that generates access patterns that hammer aggressor rows with different phases, frequencies, and amplitudes. Blacksmith finds complex patterns that trigger Rowhammer bit flips on all 40 of our recently purchased DDR4 DIMMs, $2.6 \times$ more than state of the art, and generating on average $87 \times$ more bit flips. We also demonstrate the effectiveness of these patterns on Low Power DDR4X devices. Our extensive analysis using Blacksmith further provides new insights on the properties of currently deployed TRR mitigations. We conclude that after almost a decade of research and deployed in-DRAM mitigations, we are perhaps in a worse situation than when Rowhammer was first discovered.
N T ] 1 3 M ay 2 01 3 On mod p singular modular forms

We show that an elliptic modular form with integral Fourier coefficients in a number field K, for which all but finitely many coefficients are divisible by a prime ideal p of K, is a constant modulo p. A similar property also holds for Siegel modular forms. Moreover, we define the notion of mod p singular modular forms and discuss some relations between their weights and the corresponding prime p. We discuss some examples of mod p singular modular forms arising from Eisenstein series and from theta series attached to lattices with automorphisms. Finally, we apply our results to properties mod p of Klingen-Eisenstein series.
Perceived Organizational Justice And Turnover Intention Among Secondary School Teachers In Potiskum Metropolis: A Moderating Effect Of Perceived Job Alternative

This study was examined the relationship between perceived organizational justice and turnover intention among public junior secondary school teachers. The sample consisted of 150 teachers working in 5 public junior secondary schools. Perceived organizational justice consists of three dimensions, namely, distributive, procedural and interactional justice which were used to determine the level of teachers’ performance; the study used POJ, TOI and PJA questionnaire. PPMC and regression analysis methods were used to find the relationship and the effect of PJA on TOI. The main findings of the study indicated that there is a positive and significant relationship between POJ dimensions and TOI; However, PJA was positively and significantly predicted POJ among secondary school teachers. The study provided some significant literature contributions on the POJ and TOI of secondary school teachers in Potiskum metropolis.
Compressing (Multidimensional) Learned Bloom Filters

Bloom ﬁlters are widely used data structures that compactly represent sets of elements. Querying a Bloom ﬁlter reveals if an element is not included in the underlying set or is included with a certain error rate. This membership testing can be modeled as a binary classiﬁcation problem and solved through deep learning models, leading to what is called learned Bloom ﬁlters. We have identiﬁed that the beneﬁts of learned Bloom ﬁlters are apparent only when considering a vast amount of data, and even then, there is a possibility to further reduce their memory consumption. For that reason, we introduce a lossless input compression technique that improves the memory consumption of the learned model while preserving a comparable model accuracy. We evaluate our approach and show signiﬁcant memory consumption improvements over learned Bloom ﬁlters.
Comparing immersive sound capture techniques optimized for acoustic music recording through binaural reproduction

A study was undertaken to compare three immersive sound capture techniques optimized for acoustic music recording, within the context of binaural audio reproduction. 3D audio stimuli derived from 9-channel (4+5+0) recordings of a solo piano were binaurally rendered and presented to listeners over headphones. Subjects compared these stimuli in terms of several salient perceptual auditory attributes. Results of the double-blind listening test found no significant differences between two of the sound capture techniques, “spaced” and “nearcoincident,” for the perceptual auditory attributes “envelopment,” “naturalness of sound scene,” and “naturalness of timbre. ” The spaced technique, however, was shown to create a larger virtual image of the sound source than the near-coincident technique. The coincident technique was found to create an immersive sound scene that occupies a different perceptual space from the other two techniques, delivering less envelopment and naturalness.
PREVENTION AND METHODS OF CORRECTION OF HYPERESTHESIA OF DENTAL HARD TISSUES OF TEETH

Today, periodontal diseases remain an urgent problem in dentistry, one of the symptoms of which is hyperesthesia of dental hard tissues (HDHT), the prevalence of which varies up to 98 %. Most researchers consider HDHT in periodontal diseases as a polyetiological disease, in the pathogenesis of which much attention is paid to both local and general factors. Therefore, the aim was to investigate the range of topical therapies for hard tissue hyperesthesia in periodontitis in the form of toothpastes for treatment and prevention. The design of the research included the collection of data on the range of toothpastes and the pricing policy of the studied category. 25 foreign companies present dental products on the pharmaceutical market of Ukraine. At the same time, domestic producers do not produce these products, having the ability to do so. Of the 155 units of dental care products, only 8 % belong to toothpastes with the effect of reducing the sensitivity of the teeth, which is not sufficient to meet the needs of patients. The price of imported drugs ranges from 0.42 to $ 11.77, and the purchase of these medical products in a pharmacy is beneficial to the consumer, as professional pharmaceutical care is provided.Given the mechanisms of the disease, a significant increase in the effectiveness of treatment of patients with hyperesthesia can be achieved through a comprehensive approach to eliminating its manifestations, using toothpastes.
Efficient Machine Translation with Model Pruning and Quantization

We participated in all tracks of the WMT 2021 efficient machine translation task: single-core CPU, multi-core CPU, and GPU hardware with throughput and latency conditions. Our submissions combine several efficiency strategies: knowledge distillation, a simpler simple recurrent unit (SSRU) decoder with one or two layers, lexical shortlists, smaller numerical formats, and pruning. For the CPU track, we used quantized 8-bit models. For the GPU track, we experimented with FP16 and 8-bit integers in tensorcores. Some of our submissions optimize for size via 4-bit log quantization and omitting a lexical shortlist. We have extended pruning to more parts of the network, emphasizing component- and block-level pruning that actually improves speed unlike coefficient-wise pruning.
Consumer preferences for alternative fuel vehicles in South Korea

The paper analyses consumer preferences for alternative fuel vehicles based on stated preference data gathered in South Korea. Five fuel type vehicles are considered in the analysis, and a mixed logit model using the Bayesian approach was used for the estimation. Estimation results show that preferences regarding fuel type and body type are heterogeneous, but preferences for cost variables and horsepower are relatively homogeneous across consumers. The results also show that an indirect network effect exists, influencing automobile demand. Simulation results show that diesel and hybrid vehicles will compete in the future for their shares of the market, with lower costs being the main source of competitiveness. Elasticity results show that fuel and maintenance costs are the most important factors influencing choice among alternative fuel vehicles and that an indirect network effect is important as well.
elk-Automatically Classifying Familiar Web Users From Eye-tracking Data: 1 A Machine Learning Approach

: Eye-tracking studies typically collect enormous amount of data encoding rich information about user be-4 haviours and characteristics on the web. Eye-tracking data has been proved to be useful for usability and accessibility 5 testing and for developing adaptive systems. The main objective of our work is to mine eye-tracking data with machine 6 learning algorithms to automatically detect users’ characteristics. In this paper, we focus on exploring diﬀerent machine 7 learning algorithms to automatically classify whether users are familiar or not with a web page. We present our work 8 with an eye-tracking data of 81 participants on six web pages. Our results show that by using eye-tracking features, we 9 are able to classify whether users are familiar or not with a web page with the best accuracy of approximately 72% for 10 raw data. We also show that with a re-sampling technique this accuracy can be improved more than 10%. This work 11 paves the way for using eye-tracking data for identifying familiar users that can used for diﬀerent purposes, for example 12 it can be used to better locate certain elements on pages such as adverts to meet the users’ needs or it can be used to 13 do better proﬁling of users for usability and accessibility assessment of pages. 14
Landcare in Australia: Does it Make a Difference?

Abstract Victorian landcare groups are increasingly seen as the key element of an emerging Australian success story. The assumptions underlying landcare are that limited funding of group activity will produce more aware, informed, skilled and adaptive resource managers with a stronger stewardship ethic, will increase the adoption of sustainable practices, and will assist the move to more sustainable resource use. A survey of all landholders in 12 subcatchments of north-east Victoria was undertaken in 1993 to assess the impact of landcare participation upon key programme outcomes. Information from the northeast survey indicated that landcare participation had a significant impact upon landholder awareness of issues, level of knowledge and adoption of best bet practices. This information, and earlier research by the authors, suggests that landcare group activity has made an important contribution towards sustainable resource management. However, research findings also suggested a number of flaws in programme logic. Given the low levels of profitability amongst landholders, the vast scale and intractable nature of key issues and the considerable off-site benefits of remedial action, it is problematic whether limited funding of a community development process will effect behavioural changes that are sufficient to make a difference at the landscape level. Programme emphasis upon developing landholders» stewardship ethic also appears misplaced in that there was no significant difference in the stewardship ethic of participants and non-participants. Indeed, to the extent that landcare focuses upon changing individual behaviour rather than societal barriers to rural development, landcare is open to the criticism that it places too much responsibility upon individual landholders.
Hide-and-detect: forwarding misbehaviors, attacks, and countermeasures in energy harvesting-motivated networks

Multi-scale, heterogeneous, and battery-powered Internet-of-Things (IoT) sensors and devices (later in short, nodes) have been widely deployed in diverse applications and networks. Due to the limited amount of battery energy, energy harvesting-motivated networks (EHNets) powered by immediate environmental resources are increasingly popular and rapidly emerging as the next generation of ubiquitous communication infrastructure. However, EHNets are admittedly vulnerable to a denial-of-service (DoS) attack because of the shared medium, centralized coordination, and limited computing and communicating capabilities. Because of inherent resource constraints, EHNets seldom deploying conventional heavy-weight cryptographic techniques and secure algorithms and protocols. In light of these, we first investigate energy harvesting-based networking operations and applications. Second, we analyze the different types of forwarding misbehavior and attack caused by malicious nodes and their corresponding detection strategies. We introduce a set of adversarial scenarios and visualize its communication activities to capture vulnerable scenarios and potential malicious nodes. Here, single and multiple malicious nodes colluding together are considered. Lastly, we comprehensively compare the detection strategies of forwarding misbehavior by considering six perspectives and provide future research directions with interdisciplinary points of view.