Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing Adiabatic Quantum-Flux-Parametron (AQFP) Circuits using Exact Methods

—Adiabatic Quantum-Flux-Parametron (AQFP) is a family of superconducting electronic (SCE) circuits exhibiting high energy efﬁciency. In AQFP technology, logic gates require splitters to drive multiple fanouts and both the logic gates and the splitters are clocked, requiring path balancing to ensure all fanins of a gate arrive simultaneously. There have been several attempts to optimize the resource usage of AQFP circuits under these constraints, but we identify three main shortcomings of the state of the art: i) lack of consideration for interdependent logic paths, ii) heavy reliance on balanced splitter trees, and iii) lack of support for majority-5 gates. In this work, we present a new approach of optimization for the AQFP technology that alleviates these shortcomings using exact methods. Through explicit, size-bounded enumeration, we generate a database of optimum AQFP circuits for small logic functions under different arrival time patterns of the inputs and use the resulting database to rewrite logic blocks of larger networks. We evaluate our algorithm on a subset of MCNC benchmarks. We show that the proposed method achieves over a 21% decrease in area (the number of Josephson Junctions) and a 35% decrease in delay in the critical path (the number of levels) as compared to existing work when using an area-oriented strategy. Our method achieves over a 19% area reduction when using a delay-oriented approach while decreasing delay by over 40%.
Predicting Students’ Digital Entrepreneurial intention

Abstratct - The current advancement of digital technologies has attracted the interest of many entrepreneurs providing exceptional business opportunities and digital business models which resulted in the emergence of digital entrepreneurship. In response, many researchers have conducted studies to identify the factors that impact the intention of students to become digital entrepreneurs. This paper presents a comprehensive literature review of the main factors that shape digital entrepreneurship intention among university students. The review synthesizes the findings from previous studies and highlights the importance of factors such as prior knowledge and experience in information and communication technologies (ICTs), social context, entrepreneurial training programs, and attitude towards entrepreneurship. The review concludes with implications for policy and practice to foster digital entrepreneurship among university students.
STUDENT ATTITUDE TOWARDS APPLICATION OF TECHNOLOGY ENABLED TOOLS IN AGRICULTURE EDUCATION: A CASE STUDY IN SRI LANKA INSTITUTE OF ADVANCED TECHNOLOGICAL EDUCATION DURING COVID PANDEMIC

: Higher Education and Education sector were one of the most impacted sectors with COVID -19 epidemic worldwide. For this circumstance, widely applied contingency plan was to replace the classroom education by distance teaching and learning. In such situation, student readiness and availability of technical infrastructure are paramount elements to concern; especially in a country like Sri Lanka where the technologically driven education system has not properly established yet. Therefore, present study attempted to investigate the student attitude towards technology enabled education of randomly selected 50 Agriculture students who follow higher national diploma programme in Sri Lanka Institute of Advanced Technological Education. A pre-tested survey questionnaire was employed to assess student attitude towards technology enabled education using Technology Acceptance Model (TAM) which has three main components of perceived usefulness, perceived ease of use, and perceived hedonic component. The study used Watcharawalee Lertlum and Borworn Papasratorn construct with minor modifications. Inferential and descriptive statistics were employed to analyze the data. The sample consisted with 62% (31) of female and 38% (19) of male students and, most of respondents were in average monthly income category of LKR 20000-40000. Most of them qualified with prior ICT education. The study focused the availability of technological infrastructure and found that 84% owned at least one technological device while the most popular devic e was ‘Smartphone’. In contrast, the least popular device was ‘Tablet or Notebook’. Considering the student attitude, results indicated that 82% of respondents had a high-level while, 10% and 8% had moderate and low level of attitude respectively. Further, all three components of TAM model have significant impact on willingness to apply the technology enabled tools in Agriculture education. The study implicated that providing some grants such as easy payment-based purchases, instalment purchases, work and pay basis to obtain own ICT resources are mandatory with the ICT skill development programs. And these findings could be utilized into national and institutional policy development in the arena of enabling ICT facilities into higher education sector.
ENVIRONMENTAL IMPACT ASSESSMENT FOR SUSTAINABLE TRANSPORT. IN: HANDBOOK OF TRANSPORT AND THE ENVIRONMENT

Environmental impact analysis (EIA) has been developed as a tool to address environmental issues in decisionmaking. In EIA, the environment is viewed as a system comprising human beings, flora and fauna, soil, water, air, climate, and the landscape; EIA is also concerned with interaction between these components. This chapter discusses EIA components and processes that are relevant to transport systems. Various impacts of transport projects on air quality, socioeconomics, ecology, and travel are considered and quantified so that alternative plans can be compared for their relative impact on the environment. The individual indices are converted to a combined environmental index by which different transport options can be compared. The indices can also be compared with relevant standards, and if the impact value exceeds a standard, appropriate mitigation measures can be suggested. Each of these components is dealt with in some detail.
DISCUSSION ON FROST HEAVING

MR. WATKINS DOES NOT FEEL THAT THE PAPER BY BENKELMAN AND OLMSTEAD OFFERS A COMPLETE EXPLANATION, SINCE THE PHENOMENA OBSERVED IN SOME FIVE OR SIX HUNDRED FROZEN SOIL CORES TAKEN FROM MINNESOTA SUBGRADES ARE NOT ENTIRELY EXPLAINED BY THIS THEORY. THERE SEEMS TO BE A DIFFERENCE IN THE SPACING AND THICKNESS OF THE ICE LAYERS IN THE DIFFERENT SOIL TEXTURES. A FIGURE WHICH SERVES TO EXPLAIN THE FORMATION OF THIN EVENLY SPACED ICE LAYERS IS PRESENTED. FIELD STUDIES INDICATE ICE, EXCEPT POSSIBLY HORIZONTAL ICE LAYERS, FORMS ONLY IN EXISTING VOIDS. THEREFORE, IT SEEMS THAT THE FORMATION OF THE HORIZONTAL VOID PLANES PRECEDES THE FORMATION OF THE ICE LAYERS. MR. TABER FEELS FROST HEAVING IS DUE TO THE GROWTH OF ICE CRYSTALS AND NOT TO CHANGE IN VOLUME. PRESURE IS DEVELOPED IN THE DIRECTION OF CRYSTAL GROWTH WHICH IS USUALLY DETERMINED CHIEFLY BY THE DIRECTION OF COOLING. EXCESSIVE HEAVING RESULTS WHEN WATER IS PULLED UP THROUGH THE SOIL TO BUILD UP LAYERS OR LENTICULAR MASSES OF SEGREGATED ICE THAT GROW IN THICKNESS BECAUSE WATER MOLECULES ARE PULLED INTO THE THIN FILM THAT SEPARATES THE GROWING COLUMNAR ICE CRYSTALS FROM THE UNDERLYING SOIL PARTICLES. AFTER REPEATED CYCLES OF FREEZING AND THAWING, IT WAS FOUND THAT PROMPT REFREEZING AFTER THAWING, RESULTED IN GREATER ICE SEGREGATION AND HEAVING THAN OCCURRED ON THE FIRST FREEZING. DIFFERENCES OF THESE RESULTS AS INTERPRETED BY BENKELMAN, OLMSTEAD, AND BURTON ARE DISCUSSED. THE AMOUNT OF ICE SEGREGATION AND FROST HEAVING IN SOILS IN CONTROLLED NOT ONLY BY PARTICLE SIZE, BUT ALSO BY OTHER FACTORS, SUCH AS SHAPE OF SOIL PARTICLES, COMPOSITION, AMOUNT OF WATER AVAILABLE, SIZE AND PERCENTAGE OF VOIDS, RATE OF COOLING AND MINIMUM TEMPERATURE, TENSILE STRENGTH, AND THE SURFACE LOAD OR RESISTANCE TO HEAVING. REPEATED CYCLES OF FREEZING AND THAWING INTRODUCED NO NEW FACTORS AND DO NOT ALTER THE MECHANICS OF FROST HEAVING. EXPERIMENTS SHOW THAT WITHIN CERTAIN LIMITS EXCESSIVE HEAVING TENDS TO INCREASE AS THE PARTICLE SIZE DECREASES, BUT THAT THE PRESENCE OF MUCH COLLOIDAL MATERIAL PREVENTS EXCESSIVE HEAVING BY REDUCING THE PERMEABILITY, EVEN THOUGH ICE SEGREGATION OCCURS.
CHARACTER POSITION PROCESSING 3 The Effect of Transposed-Character Distance in Chinese Reading

Previous research in alphabetic languages has shown that both position (external, internal) and distance (adjacent, non-adjacent) modulate letter position encoding during reading. To examine the generality of this pattern for a comprehensive model of word recognition and reading, we examined these effects during Chinese reading (i.e., an unspaced logographic language). Participants in two experiments read intact sentences and sentences containing transposed-character nonwords while their eye movements were monitored. Experiment 1 manipulated the distance between the transposed characters (adjacent vs. non-adjacent) within 3-character words. Reading times were longer when non-adjacent characters were transposed as compared to adjacent characters. Also, for adjacent character transpositions, a word-beginning character transposition led to longer reading times than a word-ending character transposition. Experiment 2 manipulated orthogonally character transposition distance (adjacent vs. non-adjacent) and position within 4-character words, including the beginning vs. the last character. Reading times were longer when the transposition involves the first character than when involves the ending character. Fixation durations on the target regions in the non-adjacent character transposition condition were longer than those in the adjacent character transposition condition. Taken together, these results reveal robust effects of both the initial character position and transposed-character distance in Chinese reading. Thus, the privileged status of the initial character is intrinsically related to how we access lexical information.
Premilitary Performance Evaluation of Model-mediated Telerehabilitation System with Task Stiffness Estimation

For the telerehabilitation robotic system, the stable and transparent remote therapist-patient interaction under the internet communication latency remains an open challenge. In this paper, we proposed a model-mediated telerehabilitation system to avoid the delayed force feedback on the therapist side. Moreover, a variable stiffness robot is employed in the proposed telerehabilitation system to improve the patient-robot interaction on the slave side. On the slave side, a performance-based variable stiffness interactive assistance control law was utilized and the task stiffness estimation method is designed for master-side interaction model updating. On the master side, the master subsystem was implemented by a haptic device with visual and force feedback. The overall telerehabilitation was realized by the TCP/IP internet communication method. From the premilitary experimental results, the therapist subject could conduct the therapy with the aid of visual and force feedback, and the patient subject could complete the training task with their active efforts.
Risk-adjusted Cryptocurrency Portfolio Management with Deep Reinforcement Learning Master’s Project Proposal

Portfolio management is the decision making process of continuously reallocating an amount of fund into a number of different financial investment products, aiming to maximize the return while restraining the risk [1]. There are several approaches to the problem of portfolio management which are built with different combination of methodologies and algorithms. However, there is no framework which systematically compares those approaches. There is a number of publications reviewing the field. All of those do it on the level of ideas, however. Side-by-side comparisons are lacking. Some of the existing deep machine-learning approaches attempt to predict price movements or trends [2]. In these approaches, the model outputs a predicted vector of asset prices for the next period. Then the trading agent can act upon this prediction. The performance of these price-prediction-based algorithms, however, highly depends on the degree of prediction accuracy, but it turns out that future market prices are difficult to predict. Furthermore, price predictions are not market actions, converting them into actions requires additional layer of logic [3]. Other approaches to the portfolio management problem directly optimize the policy, without explicitly predicting future prices. These model-free and fully machine-learning schemes to the algorithmic trading problem include Moody and Saffell (2001), Dempster and Leemans (2006), Cumming (2015) and the recent deep RL utilization by Deng et al. (2017) [4], [5]. These RL algorithms output discrete trading signals on a single asset. Deep RL is lately drawing much attention due to its remarkable achievements in playing video games (Mnih et al., 2015) and board games (Silver et al., 2016) [6]. A general-purpose continuous action and state space deep RL framework, the actor-critic Deterministic Policy Gradient Algorithms, was recently intro-
Give Weight to Human Reactions: Optimizing Complementary AI in Practical Human-AI Teams

With the rapid development of decision aids that are driven by AI models, the practice of human-AI joint decision making has become increasingly prevalent. To improve the human-AI team performance in decision making, earlier studies mostly focus on enhancing humans’ capability in better utilizing a given AI-driven decision aid. In this paper, we tackle this challenge through a complementary approach—we aim to adjust the designs of the AI model underlying the decision aid by taking humans’ reaction to AI into consideration. In particular, as humans are observed to accept AI advice more when their confidence in their own decision is low, we propose to train AI models with a human-confidence-based instance weighting strategy , instead of solving the standard empirical risk minimization problem. Under an assumed, threshold-based model characterizing when humans will adopt the AI advice, we first derive the optimal instance weighting strategy for training AI models. We then validate the efficacy of our proposed method in improving the human-AI joint decision making performance through systematic experimentation on both synthetic and real-world datasets.
3D Point Clouds for Documentation, Analysis and Promotion of Cultural Heritage Artifacts

New sensors and methods for recovering the 3D shape of cultural heritage can generate huge amounts of 3D data, mostly as clouds of 3D points covered by photographic texture. Such data can partially replace classic forms of documentation in cultural heritage. But in this moment in time, 3D data demonstrates its usability primarily for presentation and visualisation of cultural heritage. This is a very important and worthy goal for promotion of cultural heritage first and foremost for the general public. But how can all this digital heritage trend be used by professionals, such as archaeologists and art historians, to facilitate their principal job of interpretation and understanding of cultural heritage? Computer vision, as a part of artificial intelligence, offers many useful tools and methods for analysis of visual information. The article illustrates how some of those tools can help in the analysis of cultural artefacts in the context of underwater archaeology and monitoring of the preservation of water-logged wood. At the end, the challenges when the cultural heritage domain fully enters the big data era will be discussed.
REVIEW OF TAX COMPLIANCE: A STUDY IN INDONESIA’S TAX REFORM DURING COVID-19 PANDEMIC

: This study investigated the impact of the Indonesian strategy and normative tax reform on tax compliance. In order to investigate any possible relationship between many important aspects of tax reform on tax compliance, we are exploring about the whitleblowing system possibility affect of tax reform on tax compliance. We used 216 questionnaire from manufacture manager on listed company in Indonesia Stock Exchange during 2020, and applied multiple regression. The significance of this study is developing a new measurement of whistleblowing on tax reform for company level in Indonesia. Our results suggest that the implementation tax reform agenda in Indonesia would be associated with tax compliance. The results also show that strategy, normative and whistleblowing have a positive effect on firm‟s tax compliance, The findings identify several areas for improvements and suggest several policy implications. This applies both in direct relation to each variable or simultaneously. This study important for managers, it is necessary to prioritize this reform agenda into something tax-beneficial, for the company. And for Directorate General of Tax (DGT), the strategic, normative and whistleblowing system aspects should be adopted in the formulation of long-term tax reforms.
Forthcoming

This paper presents insights into the leadership implications of recent shifts in a range of policy contexts towards notions of collaboration and partnership. The paper draws on empirical research into the formation and operation of government instituted networks in the context of education in Victoria, Australia. From 2001, School Networks and Local Learning and Employment Networks (LLEN) were implemented by the state government to support young people in their transition through school and into employment in a context of a risk society (Beck 1992), a context where pathways into sustainable employment for young people, and others, had become more erratic. For comparative purposes, the paper also draws on published research into the implementation of joined-up approaches, including Primary Strategy Learning Networks (PSLN), in England (Moore 1 Email: annelies.kamp@canterbury.ac.nz 2 and Rutherford 2012). Using concepts from Actor Network Theory (ANT), the paper argues for the value of considering the full range of actors — both human and non-human, real and unreal — involved in networking initiatives and proposes some thoughts on the implications of such a sociology of associations for both leadership and governance.
Applications and Applied Mathematics: An International Applications and Applied Mathematics: An International Journal (AAM) Journal (AAM)

The main objective of this paper is to estimate the conditional cumulative distribution using the nonparametric kernel method for a surrogated scalar response variable given a functional random one. We introduce the new kernel type estimator for the conditional cumulative distribution function ( cond-cdf ) of this kind of data. Afterward, we estimate the quantile by inverting this estimated cond-cdf and state the asymptotic properties. The uniform almost complete convergence (with rate) of the kernel estimate of this model and the quantile estimator is established. Finally, a simulation study completed to show how our methodology can be adopted.
Design and Development of High Gain, Low Profile and Circularly Polarized Cavity-backed Slot Antennas Using High-order Modes of Square Shaped Substrtae Integrated Waveguide Resonator

In In this paper, two low profile, single fed cavity backed slot antennas providing a circularly polarized (CP) wave are introduced. One of the antennas presents a right-handed CP (RHCP) wave, while the other one offers a left handed CP (LHCP) wave. The proposed antennas consist of a square shaped Substrtae Integrated Waveguide (SIW) cavity incorporatng two couples of radiating slots to radiate two field components with 90° phase difference far from the antennas. A single layer of printed circuit board (PCB) process is employed for both antennas to provide low cost, light weight and also to be compatible with planar circuits. An inset feed line is used to excite two orthogonal modes including TE120 and TE210 with suitable phase difference for generating CP wave. Antenna structures is numerically evaluated using High Frquency Structure Simulator (HFSS) and a prototype of RHCP antenna is fabricated and its radiation charateristics including reflection coefficient, gain, Axial Ratio (AR) and radiation patterns are reported.
Pre-SVF arthroscopy : A case report of new concept of meniscus and cartilage regeneration using arthroscopy followed by intra-articular injection of adipose-derived stromal vascular fraction

Background: A series of clinical case reports demonstrating the intra-articular injection of autologous adipose-derived stem cells (The Stromal Vascular Fraction SVF) combined with platelet rich plasma (PRP), hyaluronic acid, and calcium chloride after arthroscopy procedure (Pre-SVF Arthroscopy) has a therapeutic potential to regenerate cartilage in knee osteoarthritis for elderly patient and athletes with meniscus tears as well as preventing re-tears occurrence. Case presentation: A study of three patients underwent arthroscopy procedure for unilateral knee followed by stem cells intra-articular injection that were obtained from abdominal adipose tissue by digesting lipoaspirate tissue with collagenase. The adipose-derived stem cells (Stromal Vascular Fraction SVF) were injected into the patients knee along with hyaluronic acid, platelet rich plasma and calcium chloride after the arthroscopy procedure. All patients had an injury of medial or/and lateral meniscus, osteoarthritis, history of pain and limitation of motion. Pre-treatment and post-treatment MRI scans, modified functional rate index and pain score data were then analyzed. Conclusion: Some patients may suffer from meniscus injury with symptoms such as locked knee, which may not benefit significantly with SVF intra-articular injection solely. The Pre-SVF arthroscopy procedure has shown to solve the mechanical related symptoms of the knee movement and to regenerate damage tissues, without complication or risk of early onset osteoarthritis. This clinical study conducted three patients underwent Pre-SVF arthroscopy which gain significant clinical improvement and MRI evidence of meniscus and articular cartilage regeneration.
Balancing Afforestation with Grain Production and Water Use for Sustainable Effects of Soil Conservation in the Chinese Loess Plateau

The Chinese Loess Plateau experiences the most severe soil erosion in the world, induced by the destruction of natural vegetation for cultivation. To stop soil erosion, in 1999 the Chinese government began an intensive afforestation program named Grain-for-Green-Policy in order to convert steep cultivated land to forest and grassland. Balancing afforestation with grain production and water use is crucial for obtaining sustainable effects of soil conservation. This study assessed the current balance among afforestation, grain production, and water use in river basins on the Chinese Loess Plateau. Annual afforested area, planted area of grain fields, precipitation, and irrigated area in these river basins were compared based on the data collected from the statistical yearbooks of the Yan’an City. River discharge and sediment yield in the areas were compared based on data collected from the Annual Report on Chinese Soil Conservation. The evapotranspiration rates of the main crops cultivated in each river basin were also compared. Collectively, the data suggest that the balance between afforestation, grain production, and water use has been improved by the Grain-for-Green-Policy in the river basins on the Chinese Loess Plateau.