Miracle-dz/UniFAR-FTUs huggingface dataset:
Study on Warpage and Peeling Mitigation of Wafer Level During Metal Plating Process

Wafer level packaging is one of the latest trends in microelectronic packaging. Wafer warpage and metal peeling are common problem in wafer level packaging. Large warpage and large area peeling will cause the failure of post packaging and reliability problem. The mechanism of warpage and stress are the mismatch of material's coefficient of thermal expansion (CTE) and the change of temperature in the process. In this paper, after plating a metal layer on passivation (PA) layer, there is a large wafer warpage, which makes the following process unable to continue. Based on this background, plating a metal layer on the back side of wafer is innovatively proposed to overcome warpage. The warpage and peeling of back side metallization (BSM) are also measured. The experiment also compares warpage with and without BSM. The reason of peeling, the location of peeling and the interface of peeling were studied by experiments. Based on the finite element analysis (FEA). The effect of different BSM masks on warpage and peel stress were studied. The effects of local design and BSM thickness on peel stress are also studied. Through the research of this paper. It provides guidance for the metal plating process and design of BSM, and can effectively overcome the problem of wafer warpage and peeling.
Hybrid Combining Based on Selective Activation of Double Constant Phase Shifters

In this paper, we propose a new uplink hybrid beamforming architecture for multi-user multiple-input–multiple-output (MU-MIMO) millimeter-wave (mmWave) systems. The proposed architecture employs constant phase shifters (CPSs) to control the phases of the signals in conjunction with double switches for signal selection in the radio frequency (RF) beamforming part. By using double switches to approximate the optimal double variable phase shifter (VPS)-based scheme, the proposed scheme can achieve near-optimal sum rates when the number of CPSs is large enough. In addition, with the support of the active/inactive switches, it selectively combines the antenna signals, which can further improve the sum rate while reducing power consumption. The simulation results show that the proposed scheme outperforms conventional VPS-based and fully digital combiners in terms of energy efficiency.
Gain-Scheduled Fault Detection Filter for Discrete-Time LPV Systems

The present work investigates a fault detection problem using a gain-scheduled filter for discrete-time Linear Parameter Varying systems. We assume that we cannot directly measure the scheduling parameter but, instead, it is estimated. On the one hand, this assumption imposes the challenge that the fault detection filter should perform properly even when using an inexact parameter. On the other, it avoids the burden associated with designing a complex estimation process for this parameter. We propose three design approaches: the <inline-formula> <tex-math notation="LaTeX">${\mathcal {H}_{2}}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">${\mathcal {H}_{\infty }}$ </tex-math></inline-formula>, and mixed <inline-formula> <tex-math notation="LaTeX">${\mathcal {H}_{2}} / {\mathcal {H}_{\infty }}$ </tex-math></inline-formula> gain-scheduled Fault Detection Filters designed via Linear Matrix Inequalities. We also provide numerical simulations to illustrate the applicability and performance of the proposed novel methods.
The effect of annealing time on the mechanical properties of TSV-Cu

Relying on the advantages like high density integration and stacking, through silicon via (TSV) as an advanced technology has been widely used for three-dimensional integrated circuits (3D ICs). Copper filled in through silicon via (TSV-Cu) should be annealed to eliminate defects and residual stress after electroplating, which is beneficial to improve the performance of transistors. The subsequent deformation and thermomechanical reliability of TSV devices would be affected due to the change of the mechanical properties of TSV-Cu via annealing. With the help of nanoindentation characterization and finite element method (FEM) inversion, this paper studied the stress-strain relationship of TSV-Cu on five different annealing time at 400°C. The results showed that TSV-Cu had been softened by annealing and this phenomenon would be intensified with annealing time extended. However, up to 200 min annealing time resulted in indentation load and yield strength increasing instead of decreasing. This work provided theory guide for calculating the deformation and stress of TSV structure and reducing thermomechanical reliability issues.
Evolutionary Multiobjective Feature Selection for Sentiment Analysis

Sentiment analysis is one of the prominent research areas in data mining and knowledge discovery, which has proven to be an effective technique for monitoring public opinion. The big data era with a high volume of data generated by a variety of sources has provided enhanced opportunities for utilizing sentiment analysis in various domains. In order to take best advantage of the high volume of data for accurate sentiment analysis, it is essential to clean the data before the analysis, as irrelevant or redundant data will hinder extracting valuable information. In this paper, we propose a hybrid feature selection algorithm to improve the performance of sentiment analysis tasks. Our proposed sentiment analysis approach builds a binary classification model based on two feature selection techniques: an entropy-based metric and an evolutionary algorithm. We have performed comprehensive experiments in two different domains using a benchmark dataset, Stanford Sentiment Treebank, and a real-world dataset we have created based on World Health Organization (WHO) public speeches regarding COVID-19. The proposed feature selection model is shown to achieve significant performance improvements in both datasets, increasing classification accuracy for all utilized machine learning and text representation technique combinations. Moreover, it achieves over 70% reduction in feature size, which provides efficiency in computation time and space.
Cryogenic Low-Drop-Out Regulators Fully Integrated with Quantum Dot Array in 22-nm FD-SOI CMOS

This brief presents two monolithically integrated output-capacitor-less (“caples”) low-drop-out (LDO) linear regulators implemented in 22-nm fully depleted silicon-on-insulator (FD-SOI) to support on-die scalable CMOS charge-based quantum processing unit (QPU). The proposed LDOs are used to regulate 0.8 V and 1.5 V input voltages for the programmable capacitive digital-to-analog converter (CDAC) and single-electron detector, respectively. Measured results show that both LDOs can maintain their respective output voltages with a maximum deviation <2% from ~270 K down to ~ 3.7 K.
How to maintain mental health in turbulent times: Can mobile applications be a part of the solution?

The end of 2019 and the whole of 2020 were marked by the rapid spread of the SARS-CoV-2 virus. Harsh epidemiological measures began to be applied, which led to the restriction of social contacts, and everything began to be done remotely or online. All these measures have led to the appearance of anxiety and depressive symptoms in some people. The pandemic has changed our way of life and is considered a global stressor. In 2020, Croatia was also hit by two strong devastating earthquakes, leading to anxiety and depressive symptoms in individuals, but sometimes also to PTSD in those who have suffered more severe consequences. Nowadays, almost everyone uses smartphone and many mobile applications are available (especially if they are free) that are used to improve mental health. The aim of this paper was to review the literature on mobile applications that have been used so far to improve mental health and to describe some of the advantages and disadvantages of them. The role of mental health professionals in the development of mental health mobile applications is highlighted, as well as the possibility of availability of mental health professionals in the daily use of such mobile applications (in the form of coaching). Finally, it can be concluded that a number of mobile applications are being developed that could be useful, both in acute stress and in chronic coping with anxiety and stress.
Characterizing Buffer Overflow Vulnerabilities in Large C/C++ Projects

Security vulnerabilities are present in most software systems, especially in projects with a large codebase, with several versions over the years, developed by many developers. Issues with memory management, in particular buffer overflow, are among the most frequently exploited vulnerabilities in software systems developed in C/C++. Nevertheless, most buffer overflow vulnerabilities are not detectable by vulnerability detection tools and static analysis tools (SATs). To improve vulnerability detection, we need to better understand the characteristics of such vulnerabilities and their root causes. In this study, we analyze 159 vulnerable code units from three representative projects (i.e., Linux Kernel, Mozilla, and Xen). First, the vulnerable code is characterized using the Orthogonal Defect Classification (ODC), showing that most buffer overflow vulnerabilities are related to missing or incorrect checking (e.g., missing if construct around statement or incorrect logical expression used as branch condition). Then, we run two widely used C/C++ Static Analysis Tools (SATs) (i.e., CppCheck and Flawfinder) on the vulnerable and neutral (after the vulnerability fix) versions of each code unit, showing the low effectiveness of this type of tool in detecting buffer overflow vulnerabilities. Finally, we characterize the vulnerable and neutral versions of each code unit using software metrics, demonstrating that, although such metrics are frequently used as indicators of software quality, there is no clear correlation between them and the existence of buffer overflow in the code. As a result, we highlight a set of observations that should be considered to improve the detection of buffer overflow vulnerabilities.
A Family of Quasi-Decoupled Three-Port Isolated DC-DC Converters Utilizing Asymmetric Impedances

A quasi-decoupled family of the three-port DC-DC converters for the applications requiring multiple DC power sources is proposed. The proposed topologies employ a two-level quasi-decoupling approach that combines circuit and control levels decoupling to provide enhanced freedom for manipulation of the control parameters to achieve efficient power conversion among ports. The circuit-level quasi-decoupling is achieved by a choice and configuration of the asymmetric impedances, however, control-level quasi-decoupling is realized by appropriately selecting and varying the available control parameters. The proposed topologies and control method results in a simplified power-flow control with increased freedom to vary control parameters for achieving minimum reactive current to reduce conduction loss and soft-switching to reduce switching loss. To validate the proposed quasi-decoupled topologies, a three-port DC-DC converter based on a dual-active-bridge (DAB) converter with asymmetrical impedances and optimized selection of control parameters is built for electric vehicle (EV) on-board-charger (OBC) applications.
Handling Inconsistency in Business Rule Bases

This thesis covers a wide range of aspects related to hand-ling logical inconsistency in business rule bases. In particular, this thesis presents methods and techniques for the detection, analysis and resolution of inconsistencies. The developed means were evaluated formally, integrated into open-source libraries such as bpmn.io and Camunda, and were evaluated in experiments with human participants. Here, it could be shown that the developed results allow human modellers to understand inconsistencies with a higher efficiency and less needed mental effort. The results of this thesis have been published in various conferences and journals, e.g., Artificial Intelligence (AIJ), and were awarded with the best paper award at the WI conference.
On the Notion of Maintenance State for Industrial Assets

Maintenance is vital to ensure our manufacturing assets operate safely and efficiently. Maintenance work is triggered by a number of factors. One of these factors is a change in health state of an asset and the impact of this change on the ability of the asset to perform its functions. In addition, the act of performing maintenance changes the health state of the asset, restoring or retaining it to a state in which it can perform its required function. The ability to perform maintenance can also depend on the state, up state or down state, of the asset. The notion of state and the precursors and consequence of a change in state of an asset are central to developing formal maintenance ontologies and their related reasoning mechanisms to support maintenance management process automation. This paper explores this notion in a Basic Formal Ontology (BFO) context using an illustrative case study. In modelling a simple example, we have encountered many issues that are under active discussion within the industrial ontology community. We propose a formalization for maintenance state and discuss practical and ontological issues. Our main focus is on the role of maintenance state in the interplay between function realization and process participation, conditioned on a state. The paper is a call-to-arms to the ontology community to engage with defining a notion of state to support the use of ontologies and reasoning to assist in automation of industrial manufacturing processes.
Concept-based Chatbot for Interactive Query Refinement in Product Search

Nowadays, retrieval-based dialogue engines witness a signiﬁcant interest in both industry and academic research. It is an important task to create an automated question-answering engine that may assist a user in the purchasing procedure. In this work, we describe a concept-based chatbot that utilizes a knowledge model to navigate a user to a subset of relevant objects. The knowledge model is built with pattern structures and organized to manipulate with both standard numerical and textual attributes describing the observed products. We provide an experimental evaluation of the introduced chatbot on the Flintkart e-commerce dataset and compare its performance with the faceted search approach.
Sevoflurane Increases Hippocampal Theta Oscillations and Impairs Memory Via TASK-3 Channels

Sevoflurane can induce memory impairment during clinical anesthesia; however, the underlying mechanisms are largely unknown. TASK-3 channels are one of the potential targets of sevoflurane. Accumulating evidence supports a negative role of intracranial theta rhythms (4–12 Hz) in memory formation. Here, we investigated whether TASK-3 channels contribute to sevoflurane-induced memory impairment by regulating hippocampal theta rhythms. In this study, the memory performance of mice was tested by contextual fear conditioning and inhibitory avoidance experiments. The hippocampal local field potentials (LFPs) were recorded from chronically implanted electrodes located in CA3 region. The results showed that sevoflurane concentration-dependently impaired the memory function of mice, as evidenced by the decreased time mice spent on freezing and reduced latencies for mice to enter the shock compartment. Our electrophysiological results revealed that sevoflurane also enhanced the spectral power of hippocampal LFPs (1–30 Hz), particularly in memory-related theta rhythms (4–12 Hz). These effects were mitigated by viral-mediated knockdown of TASK-3 channels in the hippocampal CA3 region. The knockdown of hippocampal TASK-3 channels significantly reduced the enhancing effect of sevoflurane on hippocampal theta rhythms and alleviated sevoflurane-induced memory impairment. Our data indicate that sevoflurane can increase hippocampal theta oscillations and impair memory function via TASK-3 channels.
Comparing Face-to-Face and Online Data Collection Methods in Preterm and Full-Term Children: An Exploratory Study

The COVID-19 pandemic has transformed the landscape for children’s daily lives and the landscape for developmental psychology research. Pandemic-related restrictions have also significantly disrupted the traditional face-to-face methods with which developmental scientists produce research. Over the past year, developmental scientists have published on the best practices for online data collection methods; however, existing studies do not provide empirical evidence comparing online methods to face-to-face methods. In this study, we tested feasibility of online methods by examining performance on a battery of standardized and experimental cognitive assessments in a combined sample of 4- to 5-year-old preterm and full-term children, some of whom completed the battery face-to-face, and some of whom completed the battery online. First, we asked how children’s performance differs between face-to-face and online format on tasks related to verbal comprehension, fluid reasoning, visual spatial, working memory, attention and executive functioning, social perception, and numerical skills. Out of eight tasks, we did not find reliable differences on five of them. Second, we explored the role of parent involvement in children’s performance in the online format. We did not find a significant effect of parent involvement on children’s performance. Exploratory analyses showed that the role of format did not vary for children at risk, specifically children born preterm. Our findings contribute to the growing body of literature examining differences and similarities across various data collection methods, as well as literature surrounding online data collection for continuing developmental psychology research.
The Position of Distractors in Multiple-Choice Test Items: The Strongest Precede the Weakest

Middle bias has been reported for responses to multiple-choice test items used in educational assessment. It has been claimed that this response bias probably occurs because test developers tend to place correct responses among middle options, tests thus presenting a middle-biased distribution of answer keys. However, this response bias could be driven by strong distractors being more frequently located among middle options. In this study, the frequency of responses to a Chilean national examination used to rank students wanting to access higher education was used to categorize distractors based on attractiveness level. The distribution of different distractor types (best distractor, non-functioning distractors…) was analyzed across 110 tests of 80 five-option items administered to assess several disciplines in five consecutive years. Results showed that the strongest distractors were more frequently found among middle options, most commonly at option C. In contrast, the weakest distractors were more frequently found at the last option (E). This pattern did not substantially vary across disciplines or years. Supplementary analyses revealed that a similar position bias for distractors could be observed in tests administered in countries other than Chile. Thus, the location of different types of distractors might provide an alternative explanation for the middle bias reported in literature for tests’ responses. Implications for test developers, test takers, and researchers in the field are discussed.
DNA-Binding Properties of YbaB, a Putative Nucleoid-Associated Protein From Caulobacter crescentus

Nucleoid-associated proteins (NAPs) or histone-like proteins (HLPs) are DNA-binding proteins present in bacteria that play an important role in nucleoid architecture and gene regulation. NAPs affect bacterial nucleoid organization via DNA bending, bridging, or forming aggregates. EbfC is a nucleoid-associated protein identified first in Borrelia burgdorferi, belonging to YbaB/EbfC family of NAPs capable of binding and altering DNA conformation. YbaB, an ortholog of EbfC found in Escherichia coli and Haemophilus influenzae, also acts as a transcriptional regulator. YbaB has a novel tweezer-like structure and binds DNA as homodimers. The homologs of YbaB are found in almost all bacterial species, suggesting a conserved function, yet the physiological role of YbaB protein in many bacteria is not well understood. In this study, we characterized the YbaB/EbfC family DNA-binding protein in Caulobacter crescentus. C. crescentus has one YbaB/EbfC family gene annotated in the genome (YbaBCc) and it shares 41% sequence identity with YbaB/EbfC family NAPs. Computational modeling revealed tweezer-like structure of YbaBCc, a characteristic of YbaB/EbfC family of NAPs. N-terminal–CFP tagged YbaBCc localized with the nucleoid and is able to compact DNA. Unlike B. burgdorferi EbfC protein, YbaBCc protein is a non-specific DNA-binding protein in C. crescentus. Moreover, YbaBCc shields DNA against enzymatic degradation. Collectively, our findings reveal that YbaBCc is a small histone-like protein and may play a role in bacterial chromosome structuring and gene regulation in C. crescentus.
Impact of Renal Function on Effectiveness and Safety Associated With Low Dose Dabigatran in Non-valve Atrial Fibrillation Patients After Catheter Ablation

Aim: The purpose of this study is to compare the effectiveness and safety of 110 mg dabigatran in non-valve atrial fibrillation (NVAF) patients with different eGFRs. Methods: We conducted a single-center retrospective cohort study to investigate the effectiveness and safety of 110 mg dabigatran for NVAF patients between January 2017 and December 2018 based on the eGFR category. Results: A total of 560 NVAF patients who treated with 110 mg dabigatran were included for analysis. In 12 months, the Kaplan-Meier survival curves indicated that the lower eGFR subgroups were more likely to experience thrombosis, bleeding, and cumulative events earlier (P = 0.021 for thrombosis; P = 0.026 for bleeding; P = 0.001 for cumulative events). Gastrointestinal bleeding occurred more frequently in the moderate group than in other groups (6.94% in the moderate group vs. 1.54% in the mild group vs. 1.22% in the normal group, P = 0.028). By multivariate analysis, chronic kidney disease (P = 0.043; OR = 4.273, 95% CI 1.043–17.543) and diabetes mellitus (P = 0.023; OR = 2.194, 95% CI 1.114–4.323) were independent predictors of the composite endpoints. A positive linear relationship was observed between eGFR levels and occurrence rate of thrombosis and bleeding under anticoagulation patients with 110 mg dabigatran (R2 = 0.432 and R2 = 0.784, respectively). Conclusions: Impaired renal function was associated with decreased safety and increased thrombosis risks in NVAF patients taking low dose dabigatran.