Miracle-dz/UniFAR-FTUs huggingface dataset:
SACQ Solder Board Level Reliability Evaluation and Life Prediction Model for Wafer Level Packages

Wafer Level Chip Scale Packaging (WLCSP) designs, including Wafer Level Fan-Out (WLFO) technologies, are gaining more and more applications for next generation small and thin devices. Since the WLCSP and WLFO packages are mounted directly on the motherboard without a substrate as a buffer, the large coefficient of thermal expansion (CTE) mismatch between the silicon die and the motherboard makes the temperature cycle board level reliability (BLR) of WLCSP and WLFO a tremendous challenge, especially for large body sizes. Currently, a tin (Sn)-silver (Ag)-copper (Cu) solder alloy such as SAC405 is commonly used in WLCSP and WLFO designs, but it has difficulty meeting the board level reliability when the footprint exceeds a certain size. As a result, a new type of solder alloy, SACQ, has been developed in recent years to enhance BLR performance. However, there is little published reliability data of how this new SACQ solder performed in actual package applications. There is also lack of a BLR life prediction model for SACQ solder, unlike the other typical eutectic or leadfree solders. In this paper, the board level temperature cycle reliability of SACQ solder is tested with various WLCSP and WLFO packages configurations. The failure modes associated with SACQ solder are evaluated in detail as well. The temperature cycle performance of SACQ solder is also compared to SAC405 solder, and shows significant improvement consistently over all the packages tested. In addition to the empirical study, a BLR life prediction model for SACQ is also developed based on finite element model (FEM). The required SACQ creep material properties, finite element model setup, damage indicator selection, and life prediction model correlation are all described with details in the paper.
Molecular strategy for detecting metastatic cancers with use of multiple tumor-specific MAGE-A genes.

BACKGROUND The human melanoma-associated antigen family A (MAGE-A) has high specificity and expression in various malignancies, but individual family members are expressed at low frequency in any one particular type of cancer. We therefore developed a method to detect mRNAs from multiple MAGE-A genes in a single reaction. METHODS Universal MAGE-A (uMAGE-A) primers and probe were designed to reverse-transcribe, amplify, and detect by electrochemiluminescence (ECL) MAGE-A mRNAs on the Origen Analyzer. The assay was performed on total RNA of melanoma (n = 9 cell lines and 24 tumors), breast cancer (n = 7 and 26), and colorectal cancer (CRC; n = 5 and 12). We also evaluated blood from melanoma (n = 50), breast cancer (n = 16), and CRC (n = 21) patients. RESULTS The uMAGE-A mRNA was detectable in 0.01-1 ng of cell line RNA. The identity of the uMAGE-A cDNA products was confirmed by sequencing and polyacrylamide gel electrophoresis. The uMAGE-A assay increased detection of melanoma, breast cancer, and CRC tumor by 13%, 31%, and 25%, respectively, compared with a MAGE-A1 assay, and by 17%, 19%, and 25%, respectively, compared with a MAGE-A3 assay. The uMAGE-A assay detected circulating tumor cells in the blood of melanoma (24%), breast cancer (25%), and CRC (29%) patients. CONCLUSIONS The uMAGE-A reverse transcription-PCR/ECL assay provides a practical and sensitive approach for detection of various metastatic cancers in tissues and blood.
The Influence of Social Support on Hematopoietic Stem Cell Transplantation Survival: A Systematic Review of Literature

Background Hematopoietic Stem cell Transplantation (HSCT) can negatively impact the psychosocial well-being of the patient. Social support is a complex term that has been variably used to encompass perceived and objective support, including caregiver presence. Social support has been associated with superior psychosocial outcomes; however the influence of social support on HSCT survival remains unclear. We sought to summarize the literature on the influence of social support on HSCT survival. Methods Medline, EMBASE, Cochrane, CINAHL, and PsycINFO were searched using the following search categories/concepts: 1) HSCT, 2) Social support, 3) Caregiver, 4) Survival, and 5) Treatment outcomes. Results We identified 6 relevant studies: 4 publications, 1 dissertation, and 1 abstract. Three studies were retrospective and 3, prospective. Sample size ranged between 92–272 with a mean/median patient age between 30–55 yrs. The duration of follow-up ranged between 13.3–48 months. Social support was measured inconsistently: 2 by retrospective investigator assessment, 2 as patients’ perceived support, 1 as caregiver presence, and 1 included caregiver presence and retrospective investigator assessment. The 4 published studies and 1 abstract demonstrate an association between better social support and survival. However, the unpublished dissertation, with the largest sample size found no association. Conclusions There is a paucity of evidence examining social support with HSCT survival. Available studies are older, with the most recent publication in 2005. A heterogeneous group of HSCT patients were studied with variable follow-up times. Further, covariates were variably considered in HSCT survival analyses and we suggest that there may be publication bias, given the negative unpublished study with the largest sample size. Prospective studies using validated scales are necessary to better assess the influence of social support on HSCT mortality. Given the potential for improved HSCT survival with better social support, HSCT centres should routinely provide HSCT recipients and their caregivers with enhanced psychosocial services.
Coherent Transport in Photonic Lattices: A Survey of Recent Analytic Results

The analytic specifications of photonic lattices with fractional revival (FR) and perfect state transfer (PST) are reviewed. The approach to their design which is based on orthogonal polynomials is highlighted. A compendium of analytic models with PST is offered. New results on their FR properties are included. The nearest-neighbour approximation is adopted in most of the review; one analytic example with next-to-nearest neighbour interactions is also presented.
Social inclusion of children with complex needs in mainstream: does visibility and severity of disability matter?

Objectives: Many children with complex needs (CN) are now educated in mainstream schools with social inclusion as a primary aim. However, evidence for positive outcomes is inconclusive, and a range of factors have been implicated, including the visibility and severity of a child's disability and the adequacy of support provided. Methods: This study assessed the social inclusion by 528 typical classmates of 20 children with CN attending mainstream schools supported by an outreach service. Sociometry was used to assess dimensions of social inclusion in relation to the visibility and severity of a child's disability. Results: Children with CN were found to have equivalent social inclusion to their mainstream classmates. Social acceptance was found to be associated with the visibility but not the severity of a child's disability. Conclusion: Visibility of disability may be important to consider when planning social inclusion support. Paradoxically, children with less visible disabilities may require greater social inclusion support than their peers with more obvious needs.
Hierarchical secret image sharing method using JPEG 2000 codestream syntax

This paper proposes a hierarchical secret sharing method for image data. In the conventional secret sharing scheme (SSS), secret data is reconstructed only if more shares are gathered and combine than a pre-decided number, k. Though large k makes a strong security feature, it creates problems with the handling of the many shares required to reconstruct the original data. If it allows us to browse the contents of secret image data roughly, then it relieves us from the troublesome management of the secret data. Therefore, in order to improve usability, we propose a new SSS using JPEG 2000's hierarchical image representation. This method can control the number of reconstructed frequency sub-bands of image information by the number of combined shares. It can also control the precision of pixel values and the reconstructed region in the image. This paper shows the feasibility and efficiency of the proposed method by computer simulations.
End-user development ( EUD )

Computer users have rapidly increased in both number and diversity (Scaffidi, Shaw and Myers, 2005). Many of these people work on tasks that rapidly vary on a yearly, monthly, or even daily basis. Consequently, their software needs are diverse, complex, and frequently changing. Professional software developers cannot directly meet all of these needs because of their limited domain knowledge and because their development processes are too slow. End-user development (EUD) helps to solve this problem. EUD is " a set of methods, techniques and tools that allow users of software systems, who are acting as non-professional software developers, at some point to create, modify, or extend a software artifact " (Lieberman, Paterno, Klann, and Wulf 2006). In particular, EUD enables end users to design or customize the user interface and functionality of software. This is valuable because end users know their own context and needs better than anybody else, and they often have real-time awareness of shifts in their respective domains. Through EUD, end users can tune software to fit their requirements more closely than would be possible without EUD. Moreover, because end users outnumber professional software developers by a factor of 30-to-1 (Figure 1), EUD " scales out " software development activities by enabling a much larger pool of people to participate. However, EUD is inherently different from traditional software development, and trying to support EUD by simply mimicking traditional approaches is often insufficient to produce successful results. End users usually do not have training in professionals' programming languages, formal development processes, or modeling and diagramming notations. Moreover, end users often lack the time or motivation to learn these traditional techniques, since end users usually write code in order to achieve a short-or medium-term goal rather than to create a durable software asset that will produce a continuing revenue stream. Consequently, supporting EUD requires providing appropriate tools, social structures, and development processes that are highly usable, quickly learned, and easily integrated into domain practice. EUD overlaps with two similar concepts, end-user programming and end-user software engineering. End-user programming (EUP) enables end users to create their own programs (Ko et al, 2011). This subset of EUD is the most mature from a research and practice perspective, so we focus a later section of this article on that portion of EUD. The difference between EUP and EUD is that EUD methods, techniques, and tools span the entire software development lifecycle, including …
Comparative study of PEGASIS based protocols in wireless sensor netwroks

A comparative study involves comparison of protocols based on some performance parameters. It helps researchers to get insight into the different parameters in relevance with the protocols which ultimately lead the way to the further advancement in the field. As improvements in the field of Wireless Sensor Networks are taking place day by day. PEGASIS is a hierarchical chain oriented protocol for routing in WSN. In this paper, some important protocols based on PEGASIS architecture; PEGASIS, EEPB, IEEPB, PDCH, PEG-Ant, PEGASIS-PBCA, PEGASIS-IBCA, MH-PEGASIS, Multi-chain PEGASIS and Modified-PEGASIS are studied and comparison is done based on parameters which are important to consider while choosing methodology for a particular application of WSNs.
Long-Term Memory Networks for Question Answering

Question answering is an important and difficult task in the natural language processing domain, because many basic natural language processing tasks can be cast into a question answering task. Several deep neural network architectures have been developed recently, which employ memory and inference components to memorize and reason over text information, and generate answers to questions. However, a major drawback of many such models is that they are capable of only generating single-word answers. In addition, they require large amount of training data to generate accurate answers. In this paper, we introduce the Long-Term Memory Network (LTMN), which incorporates both an external memory module and a Long Short-Term Memory (LSTM) module to comprehend the input data and generate multi-word answers. The LTMN model can be trained end-to-end using back-propagation and requires minimal supervision. We test our model on two synthetic data sets (based on Facebook's bAbI data set) and the real-world Stanford question answering data set, and show that it can achieve state-of-the-art performance.
Voice Quality Variation and the Perception of Affect: Continuous or Categorical?

This paper explores the mapping of voice quality to affect, for a synthesised tense – lax voice continuum. Two questions are of interest. Firstly, over such a continuum, do listeners’ attributions of affect change in a continuous or in a more categorical way? Secondly, might discreetly different affects emerge at different points in the continuum: specifically, might a moderately tense voice cue happy? Note that extremely tense does not appear to, but seems rather to be associated with the affect angry. A continuum of stimuli were synthesised ranging from a very tense quality at one end to a very lax quality at the other. Listeners rated their affective colouring in terms of the pairs of affective attributes: stressed/relaxed, angry/content, happy/sad, interested/bored, formal/intimate, and indignant/apologetic. Results suggest that, for these voice qualities, listeners’ attribution of affect is essentially continuous. Furthermore, moderate tension does not evoke happy.
Diet and Human Mobility from the Lapita to the Early Historic Period on Uripiv Island, Northeast Malakula, Vanuatu

Vanuatu was first settled ca. 3000 years ago by populations associated with the Lapita culture. Models of diet, subsistence practices, and human interaction for the Lapita and subsequent occupation periods have been developed mainly using the available archaeological and paleoenvironmental data. We test these models using stable (carbon, nitrogen, and sulfur) and radiogenic (strontium) isotopes to assess the diet and childhood residency of past communities that lived on the small (<1 km2) island of Uripiv, located off the northeast coast of Malakula, Vanuatu. The burials are from the initial Lapita occupation of the island (ca. 2800–2600 BP), the subsequent later Lapita (LL, ca. 2600–2500 BP) and post-Lapita (PL, ca. 2500–2000 BP) occupations, in addition to a late prehistoric/historic (LPH, ca. 300–150 BP) occupation period. The human stable isotope results indicate a progressively more terrestrial diet over time, which supports the archaeological model of an intensification of horticultural and arboricultural systems as local resources were depleted, populations grew, and cultural situations changed. Pig diets were similar and included marine foods during the Lapita and PL periods but were highly terrestrial during the LPH period. This dietary pattern indicates that there was little variation in animal husbandry methods during the first 800 years of prehistory; however, there was a subsequent change as animal diets became more controlled in the LPH period. After comparison with the local bioavailable 87Sr/86Sr baseline, all of the Lapita and LPH individuals appeared to be ‘local’, but three of the PL individuals were identified as “non-local. ” We suggest that these “non-locals” moved to the island after infancy or childhood from one of the larger islands, supporting the model of a high level of regional interaction during the post-Lapita period.
An Empirical Comparison of Unknown Word Prediction Methods

We compare two types of methods which deal with unknown words in the context of computational grammars. Methods of the first type are based on the idea of supertagging and use a tagger to predict lexical descriptions for unknown tokens in a given input. The second type of methods perform lexical acquisition (LA) which, in the context of this paper, refers to the automatic acquisition of new lexical entries for the lexicon of a given grammar. The methods are compared based on the effect their application has on the parsing coverage and accuracy of the GG grammar of German (Crysmann, 2003). In particular, we adapt the LA method of Cholakov and van Noord (2010) which was originally developed for the Dutch Alpino system to be used with the GG. Its impact on coverage and accuracy on a test corpus of German newspaper texts is compared to the results reported previously on the same corpus for methods which employed a tagger. Furthermore, in a smaller experiment, we show that the linguistic knowledge this LA method provides can also be used for sentence realisation.
When there is no speech : a case study of the nonverbal multimodal communication of a child with an intellectual disability

This case study uses Systemic Functional theory to describe and analyse the multimodal communication of an eight year-old boy, Bodhi, with both a severe intellectual disability and a severe communication impairment. The study specifically explores the meanings Bodhi makes and the resources he uses instead of speech to make those meanings. The study also examines the underlying system of language Bodhi draws on to make his meanings. The theoretical resources of the Systemic Functional model of language are used to capture both what occurs within Bodhi’s communicative turns and also what occurs across the turns at the level of discourse semantics. Within the turn, the study uses the theoretical resources of the interpersonal, ideational and textual metafunctions; above the turn, the study uses the resources of Exchange Structure Analysis. The corpus consists of data collected via tape recorder and observation notes. In order to capture the effects of different communication partners on the interactions with Bodhi, data collected via tape recorder consists of two transcripts of Bodhi communicating with different communication partners, his father and his grandmother. Each transcript was segmented into exchanges and moves. These were quantified to expose patterns of communication. Each move was examined for the presence of metafunctional meanings, which were also quantified. The study demonstrates that Bodhi makes meaning in ways that are different to speakers (of English). The findings also show that while he occupies a restricted semiotic space, having what could be construed as a form of protolanguage, Bodhi’s communication also has features of transition and adult language. The study also shows that while Bodhi is a persistent communicator, intent on getting his meanings across, contributions of the communication partner are crucial for the success of Bodhi’s meaning making. This success relies on a willingness on the part of the communication partner to work together with Bodhi in the joint negotiation and joint construction of meaning. This study also identifies a lack of research within the field of Augmentative and Alternative Communication that describes the meaning making of ambulant nonverbal multimodal communicators with severe intellectual disabilities. The study also provides an opportunity for understanding how the ‘other’, the nonverbal multimodal communicator makes meaning.
Fast Detection of Multi-View Face and Eye Based on Cascaded Classifier

In our multi-view face and eye detection, we use a cascaded classifier trained by gentle AdaBoost algorithm, one of the appearance-based pattern learning method. Specifically, in order to detect multi-view face, we propose a special cascaded classifier using coarse-to-fine search, simple-to-complex search, and parallel-to-separated search. In order to detect eye, we propose a four-step eye detection method. Using proposed methods, we got face and eye detection ratios as 99.5%, 88.3%, respectively for 7 different DBs including 17,018 various multi-view faces.
Group ranking with application to image retrieval

Many existing ranking-related information processing applications can be summarized into one theoretical problem called group ranking (GR). A simple average-ranking approach is usually applied to GR. Although the approach seems reasonable, no theoretical analysis about its intrinsic mechanism has been presented, increasing the difficulty of evaluating the ranking results. This study provides a formal analysis for GR. We first construct an objective function for the GR problem, and discover that each GR problem can be transformed into a rank aggregation problem whose objective function is proved to be equal to the objective function of GR. As a consequence, the average-ranking approach can be explained by two well-known rank aggregation techniques. We incorporate two other effective rank aggregation methods into the GR problem and obtain two new GR algorithms. We apply the GR algorithms into image retrieval to diversify the image search results returned by search engines. Experimental results show the effectiveness of the proposed GR algorithms.
Hierarchical Z-buffer visibility

An ideal visibility algorithm should a) quickly reject most of the hidden geometry in a model and b) exploit the spatial and perhaps temporal coherence of the images being generated. Ray casting with spatial subdivision does well on criterion (a), but poorly on criterion (b). Traditional Z-buffer scan conversion does well on criterion (b), but poorly on criterion (a). Here we present a hierarchical Z-buffer scan-conversion algorithm that does well on both criteria. The method uses two hierarchical data structures, an object-space octree and an image-space Z pyramid, to accelerate scan conversion. The two hierarchical data structures make it possible to reject hidden geometry very rapidly while rendering visible geometry with the speed of scan conversion. For animation, the algorithm is also able to exploit temporal coherence. The method is well suited to models with high depth complexity, achieving orders of magnitude acceleration in some cases compared to ordinary Z-buffer scan conversion.
Reconstruction of surveillance videos by non-iterative pseudo inverse based recovery algorithm (NIPIRA): A subjective experience

Compressed sensing is a conceptual process where the input data is compressed to a lower dimensional vector i.e. M ≤ N. Perfect recovery of the original data from these diminished measurements is carried out using various recovery procedures. Many of the procedures are iterative in nature that introduce complications such as computational complexity, increased elaspsed time etc. Hence Non-Iterative pseudo inverse based recovery algorithm (NIPIRA) is formulated to face the above said discrepancies effectively. The recovery of surveillance videos has been carried out perfectly using NIPIRA and the recovered videos are subjectively evaluated with the help of naive viewers. Mean opinion score (MOS) for 8 recovered surveillance videos, under various low level attributes and abstract attributes, are collected from 20 naive viewers. The average score given by the scorers is around 4.5 denoting the `Excellent' range in MOS table proving NIPIRA to be the best algorithm for recovery of videos from compressively sensed measurements.