Miracle-dz/UniFAR-FTUs huggingface dataset:
Memory-Aware Functional IR for Higher-Level Synthesis of Accelerators

Specialized accelerators deliver orders of a magnitude of higher performance than general-purpose processors. The ever-changing nature of modern workloads is pushing the adoption of Field Programmable Gate Arrays (FPGAs) as the substrate of choice. However, FPGAs are hard to program directly using Hardware Description Languages (HDLs). Even modern high-level HDLs, e.g., Spatial and Chisel, still require hardware expertise. This article adopts functional programming concepts to provide a hardware-agnostic higher-level programming abstraction. During synthesis, these abstractions are mechanically lowered into a functional Intermediate Representation (IR) that defines a specific hardware design point. This novel IR expresses different forms of parallelism and standard memory features such as asynchronous off-chip memories or synchronous on-chip buffers. Exposing such features at the IR level is essential for achieving high performance. The viability of this approach is demonstrated on two stencil computations and by exploring the optimization space of matrix-matrix multiplication. Starting from a high-level representation for these algorithms, our compiler produces low-level VHSIC Hardware Description Language (VHDL) code automatically. Several design points are evaluated on an Intel Arria 10 FPGA, demonstrating the ability of the IR to exploit different hardware features. This article also shows that the designs produced are competitive with highly tuned OpenCL implementations and outperform hardware-agnostic OpenCL code.
Cyber-physical production system assessment within the manufacturing industries in the Amazon

Cyber-physical production systems (CPPS) represent a relevant aspect related to industry 4.0 and the advances promoted by the digitization and use of artificial intelligence in the production environment in the search for the development of smart factories. This study aims to assess the maturity level of cyber-physical production system (CPPS) within manufacturing industries in the Amazon. The research uses a quali-quantitative approach to analyze the problem by conducting exploratory case studies (indepth case) and the research framework used aimed to evaluate and measure the CPPS within three manufacturing industries in the Amazon (n = 3) to measure their maturity. Findings reveal a positive relationship between the type of production system adopted by the company, the level of automation, and the maturity of the CPPS. The proposed methodology can assist other companies in the development of the technological strategy, supporting the digital transformation process in order to obtain competitive advantage. The study contributes by addressing the topic of cyber-physical production systems from the point of view of operations management and strategy.
Continuous frequency and isolation reconfigurable MIMO PIFA antennas using liquid materials

In this paper, a continuous frequency and isolation reconfigurable multiple input multiple output (MIMO) PIFA antenna loaded with a decoupled neutralization line structure is proposed. A pair of transparent boxes made of PC material was loaded between the radiation plane and the ground to provide conditions for reconfiguration. The frequency reconfigurable range is from 1.58 GHz to 1.08 GHz (frequency tuning range 37.5%) which is achieved by controlling the height of pure water from 0 mm to 9.15 mm. Pure water in the PC box will interfere with the electric field distribution near the antenna and change the effective dielectric constant of the dielectric. In the range of 1.08 ~ 1.58 GHz continuous frequency reconfigurable, the load of neutralization line makes the mutual coupling of working frequency band decreases by at least 8 dB. And the antenna prototype is measured. The simulation results are in good agreement with the measured results, which verifies the feasibility of this technology.
fMRI Food Cue Reactivity as a Predictor for BMI Change Following Roux-en-Y Gastric Bypass (RYGB) or Diet Intervention

Prevalence of severe obesity continues to increase, with only bariatric surgery showing long-term efficacy for sustained weight loss. Individuals with severe obesity (vs normal weight) show greater fMRI responsivity to high energy dense (ED) vs low ED food cues and reduced responsivity post-surgery. We examined responsivity to high vs low ED cues pre-intervention in association with postsurgical (RYGB) or dietary weight-loss (dWL) change in BMI at 4 and 18 mo. Region of interest (ROI) analysis employed separate ANCOVA models; group as single factor with three levels and baseline activation and interaction with group covarying for age and gender as nuisance covariates. Significant results were identified at p < 0.1 false discovery rate (FDR) corrected, following multiple comparisons across ROIs. In the precentral gyrus (motor and motor readiness area), higher baseline activation was associated with greater %BMI reduction in RYGB at 4 and 18 mo and less %BMI reduction in dWL at 4 mo (p = 0.006 uncorrected, P < 0.1 FDR corrected). The findings show opposite directionality in predicting change in BMI for RYGB vs. dWL from responsivity to high vs low ED food cues in the precentral gyrus. Greater baseline motor planning to ingest high ED foods may be associated with reduced weight loss in dWL, and with greater weight loss in RYGB due to neuromodulatory effects of surgery.
A Survey on the High-Performance Computation of Persistent Homology

Persistent Homology is a computational method of data mining in the field of Topological Data Analysis. Large-scale data analysis with persistent homology is computationally expensive and memory intensive. The performance of persistent homology has been rigorously studied to optimize data encoding and intermediate data structures for high-performance computation. This paper provides an application-centric survey of the High-Performance Computation of Persistent Homology. Computational topology concepts are reviewed and detailed for a broad data science and engineering audience.
Water Profitability Analysis to Improve Food Security and Climate Resilience: A Case Study in the Egyptian Nile Delta

The food self-sufficiency policy has always featured as an unquestionable policy objective for Egypt. This is understandable when one considers both the high population growth and the social and political vulnerability associated with a dependence on food imports and world market food prices such as wheat. Intensive agriculture has led to a growing subsidy burden for the Egyptian government. In addition, the agricultural fields in Egypt are commonly distributed with relatively small sizes parcels that usually reduce the reliability of the agricultural sector, particularly in the delta region, to meet the national food policy. On top of that, climate change, through changing weather patterns and increased temperatures, is affecting agricultural yields and thus farmers’ livelihoods. A water profitability analysis was conducted for three governorates in the Nile Delta in Egypt to establish a baseline and assess the net return per unit of water of the main crops in each of these governorates; this can act as a reference of the water profitability of different crops before they are affected by climate change and other internal and external factors. The analysis was based on extensive in-person surveys in each governorate in addition to workshop discussions with farmers. The study has highlighted the impact of a lack of extension services, which limits farmers’ ability to increase their land and water productivity. Farmers with more access to subsidized production inputs managed to achieve higher levels of water profitability even on smaller lands. Finally, we drew from our findings key policy actions to improve water profitability and land productivity for farmers in the Nile Delta to achieve higher levels of food security. This will help build resilient food production systems that are reliable in the face of climate change and other drivers. In addition, an integrated nexus strategy and plan for the inter- and intra-country is recommended to address the challenges related to food and climate security.
First record of Calotesvindumbarbatus Wagner, Ihlow, Hartmann, Flecks, Schmitz & Böhme, 2021 (Squamata: Agamidae) from China, with revised diagnosis of this species

Abstract Background Three new species were recently described from the Calotesmystaceus Duméril & Bibron, 1837 complex. Of the three new species, C.vindumbarbatus Wagner, Ihlow, Hartmann, Flecks, Schmitz & Böhme, 2021 was known only from northern Myanmar. New information Seven specimens of lizard were collected from Tongbiguan Nature Reserve, western Yunnan, China. Phylogenetically, these specimens clustered with the type specimens of Calotesvindumbarbatus from Myanmar with strong support and showed inappreciable genetic divergence from the type specimens of C.vindumbarbatus. We report the first country record of C.vindumbarbatus from China. In addition, a supplementary description, based on the newly-collected specimens and revised diagnosis of this species, was provided.
School Leadership during the COVID-19 Crisis: A Preliminary Case Study from China

This paper presents the initial findings of how a Chinese school leader employed educational leadership over an early period during the coronavirus disease 2019 (COVID-19) crisis. The reported research is one case study, part of a larger study that aims to uncover how school leaders in a variety of international contexts, namely China, Bolivia, and Western Australia, managed and responded to the COVID-19 crisis. Qualitative data collection methods were employed to develop insights into the extent to which school leaders’ roles and approaches to leadership changed over the course of the crisis as well as how the leaders’ approaches were influenced by different contextual factors. This paper focuses on initial findings from one case within the Chinese context which indicate that the school leader’s role and leadership approach was centred on supporting student learning, responding to the needs of student wellbeing, and managing parental concerns and needs, which was supported by the school’s teaching staff. Additionally, the paper shows how different contextual factors, more specifically the wider educational system and the parents, influenced the leader’s response to the COVID-19 at the school level. The study offers important insights into how school leaders responded to the disruptive challenge of COVID-19 and the contextual factors that influenced a leader’s approach. Furthermore, the Wei Zhang, Michelle Striepe & Christine Cunningham 226 findings will contribute to current theoretical understandings about educational leadership during times of crisis.
Optimal inter-stimulus interval for interpolated twitch technique when using double pulse stimulation

Optimal inter-stimulus interval for Interpolated twitch technique when using double pulse stimulation. Interpolated twitch technique is a method frequently used to assess voluntary activation. This method uses electrically evoked twitch superimposed on the voluntary activity and its comparison with the twitch in rested muscle i.e. control twitch, to evaluate completeness of muscle activation. The purpose of this study was to investigate the effect of interval in paired stimulation on control twitch in young and elderly individuals with bent and flexed knee positions. Supramaximal electrical stimulation consisted of one single stimulus and eight paired stimulation with intervals from 5 to 40ms, with increments of 5ms. In evoked twitches normalized peak torque amplitude (NPT), time to peak torque (TPT), half-relaxation time (HRT), maximal rate of torque development (RTD) were calculated. Although all parameters were slightly different in young adults compared to elder ones, the difference reached significance only in shorter TPT and HRT for the former, a phenomenon attributed to the slowing of muscle contractile mechanics with ageing. In both groups the highest RTD and NPT were observed with shorter inter-stimulus intervals i.e. 5 and 10ms. This may be attributed to a summation effect and/or a less time available for the longer-latency reflex effects of electrical stimulation to affect the torque. Contents 1 Introduction . 6 2 Interpolated Twitch Technique: . 7 2.1 Quantifying voluntary activation . 7 2.1. 1 Voluntary activation index . 7 2.1. 2 Extrapolating the evoked-voluntary force relationship . 9 2.1. 3 Central activation ratio: . 10 2.1. 4 Limitation . 11 2.2 Applications . 12 2.3 Effect of number of stimuli on ITT . 16 Mechanism of effect of stimulation mode . 18 3 Muscle Fiber Conduction Velocity . 19 3.1 Effect of ageing . 20 3.2 Effect of fatigue . 22 4 Aim of Study . 24 5 Methods . 24 5.1 Subjects . 24 5.2 Experimental Design . 25 5.3 Procedures . 25 5.4 Data collection . 26 5.5 Data Analysis . 26 5.6 Statistical Analysis . 27 6 Results . 27 6.1 Normalized Peak Twitch Torque . 27 6.2 Maximal Rate of Torque Development . 29 6.3 Time to Peak Torque . 31 6.4 Half Relaxation Time . 33 7 Discussion . 35 8 References: . 39
Reinforcement learning based optimal decision making towards product lifecycle sustainability

ABSTRACT Artificial intelligence (AI) has been widely used in robotics, automation, finance, healthcare, etc. However, using AI for decision-making in sustainable product lifecycle operations is still challenging. One major challenge relates to the scarcity and uncertainties of data across the product lifecycle. This paper aims to develop a method that can adopt the most suitable AI techniques to support decision-making for sustainable operations based on the available lifecycle data. It identifies the key lifecycle stages in which AI, especially reinforcement learning (RL), can support decision-making. Then, a generalised procedure of using RL for decision support is proposed based on available lifecycle data, such as operation and maintenance data. The method has been validated in a case study of an international vehicle manufacturer, combined with modelling and simulation. The case study demonstrates the effectiveness of the method and identifies that RL is the current most appropriate method for maintenance scheduling based on limited available lifecycle data. This paper contributes to knowledge by demonstrating an empirically grounded industrial case using RL to optimise decision-making for improved product lifecycle sustainability by effectively prolonging the product lifetime and reducing environmental impact.
Strategies to Reduce Mental Illness Stigma: Perspectives of People with Lived Experience and Caregivers

Background: Reducing the stigma surrounding mental illness is a global public health priority. Traditionally, anti-stigma campaigns were led by mental health professionals/organisations and had an emphasis on increasing mental health literacy. More recently, it has been argued that people with lived experience have much to contribute in terms of extending and strengthening these efforts. The purpose of this paper was to elicit views and suggestions from people with lived experience (PWLE) as well as from informal caregivers of people with mental health conditions, on effective strategies to combat the stigma surrounding mental illness. Methods: Six focus group discussions (FGDs) were carried out with PWLE recruited at outpatient services at the Institute of Mental Health, Singapore, and five FGDs were carried out with informal caregivers who responded to advertisements for the study between March and November 2018. In all, the sample comprised 42 PWLE and 31 caregivers. All the FGDs were transcribed verbatim and were analysed using thematic analysis. A pragmatic approach was adopted for the study, and the researchers did not assume any particular philosophical orientation. Results: Four overarching themes depicting strategies to combat stigma were identified through thematic analysis. They were (1) raising mental health awareness, (2) social contact, (3) advocacy by influential figures or groups, and (4) the legislation of anti-discriminatory laws. Conclusions: These strategies were in line with approaches that have been used internationally to disrupt the process of stigma. Our study has further identified nuanced details on how these strategies can be carried out as well as possible areas of priority in the Singapore landscape.
Achieving Fulfilment in Life: Cultivating the Mindset of Gratitude Among Thai Adolescents

Gratitude plays a significant role in nurturing holistic health and wellbeing in adolescent. However, cultivating the mindset of gratitude is associated with several factors, in particular, culture and religion. Therefore, an opportunity exists for studies to be undertaken, exploring gratitude specifically within the Thai culture. This grounded theory study aimed to understand how Thai adolescents cultivated a mindset of gratitude. Data were gathered from 27 participants, aged 15 to 19 years. Purposeful and theoretical sampling techniques were used to select participants. Data were collected through in-depth interviews, written stories, and drawn pictures. Data analysis was guided by Strauss and Corbin’s grounded theory. The core category of “Achieving Fulfilment in Life”—reflecting the process of cultivating the mindset of gratitude among Thai adolescents—comprised three categories: (a) condition: appreciating the value of oneself and others; (b) strategies: committing to live life on a positive life path; and (c) consequence: attaining true happiness. The findings illustrated the processes involved in cultivating the mindset of gratitude, highlighting how this may help in the development of a holistic health promotion program using the concept of gratitude to enhance the health and wellbeing of adolescents.
Continuous Improvement Of Engineering Technology Programs Coming Soon To A University Near You

While engineering technology programs have long had input from alumni, employers and industrial advisory committees, few departments have had a formal continuous improvement program in place. Continuous improvement has become a key component in the quality system of many businesses striving for a competitive edge. Research shows that no matter how solid an organization’s foundation, if the organization does not continually improve, it will be surpassed by more ambitious competitors and begin to loose its customer base. Educational organizations are no exception. Realizing this, the Technology Accreditation Commission of the Accreditation Board for Engineering and Technology (TAC/ABET) has added continuous improvement into accreditation requirements for engineering technology programs. Program evaluation has been changing to increasingly emphasize the concept. The Engineering Accreditation Commission of the Accreditation Board for Engineering and Technology (EAC/ABET) was first to replace prescriptive accreditation requirements with outcome-based, assessment-driven objectives defined by the stakeholders in each program in its Engineering Criteria 2000 (EC 2000). This paper will discuss what it means to establish a formal continuous improvement program and how the concept can be applied to engineering technology education. It will discuss various methods of assessment and continuous improvement efforts underway at Purdue University Calumet.
A Risk-Based Approach in Rehabilitation of Water Distribution Networks

A risk-based approach to support water utilities in terms of defining pipe rehabilitation priorities is presented. In a risk analysis in the risk management process, the probability that a given event will happen and the consequences if it does happen have to be estimated and combined. In the quantitative risk analysis, numerical values are assigned to both consequence and probability. In this study, the risk event addressed was the inability to supply water due to pipe breaks. Therefore, on the probability side, the probability of pipes breaking was assessed, and on the consequence side, the reduced ability to satisfy the water demand (hydraulic reliability) due to pipe breakage was computed. Random Forest analysis was implemented for the probability side, while the Asset Vulnerability Analysis Toolkit was used to analyse the network’s hydraulic reliability. Pipes could then be ranked based on the corresponding risk magnitude, thereby feeding a risk evaluation step; at this step, decisions are made concerning which risks need treatment, and also concerning the treatment priorities, i.e., rehabilitation priorities. The water distribution network of Trondheim, Norway, was used as a case study area, and this study illustrates how the developed method aids the development of a risk-based rehabilitation plan.
Exploring Spillover Effects for COVID-19 Cascade Prediction

An information outbreak occurs on social media along with the COVID-19 pandemic and leads to an infodemic. Predicting the popularity of online content, known as cascade prediction, allows for not only catching in advance information that deserves attention, but also identifying false information that will widely spread and require quick response to mitigate its negative impact. Among the various information diffusion patterns leveraged in previous works, the spillover effect of the information exposed to users on their decisions to participate in diffusing certain information has not been studied. In this paper, we focus on the diffusion of information related to COVID-19 preventive measures due to its special role in consolidating public efforts to slow down the spread of the virus. Through our collected Twitter dataset, we validate the existence of the spillover effects. Building on this finding, we propose extensions to three cascade prediction methods based on Graph Neural Networks (GNNs). Experiments conducted on our dataset demonstrated that the use of the identified spillover effects significantly improves the state-of-the-art GNN methods in predicting the popularity of not only preventive measure messages, but also other COVID-19 messages.
Finite element analysis on vacuum microelectronic acceleration sensor

The theory of the vacuum microelectronic acceleration sensor and the corresponding structures and the mechanisms are discussed through the finite element method to analyze the static and kinetic behavior of the processed mass. The results of the relation curves describe the relationships of the dimensions vs maximum motion of the mass, the dimensions vs resonant frequency, the forced vibration responding of the mass. All these analysis are helpful to design such acceleration sensors.