Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Interconnect Shape and Thermal-Electro-Migration on Solder Creep of Copper-Pillar Flip Chip Joints

With the development of electronic products toward high density and high reliability, the size of interconnect solder joints and interconnect pitch continues to decrease. Under normal service conditions, solder joints are subjected to thermal–electric–mechanical loads simultaneously, resulting in reliability problems for many package structures. This article investigated the effects of interconnect shape and thermal-electro-migration on solder creep of copper-pillar flip chip joints and analyzed the corresponding failure modes and mechanisms. In this article, solder joints with different shapes were obtained by adjusting the thermal compression bonding process parameters, and creep experiments were performed on the solder joints under different temperature and stress conditions. In addition, we have performed thermoelectric coupling experiments and finite element simulations for different shapes of solder joints. Moreover, creep experiments were conducted on three types of solder joints after 10 and 40 h of thermoelectric coupling pretreatment. The results show that the three solder joints exhibit typical creep characteristics under different experimental conditions and the creep strain rate increases with the increase of shear stress and temperature. Under the same conditions, the creep strain rate of the hourglass-shaped solder joint is always higher than that of the other two solder joints. The electromigration reliability of the hourglass-shaped solder joint is the worst, and the electromigration reliability of the cylinder-shaped solder joint is the best. With the increase of thermoelectric coupling pretreatment time, the creep strain rate of solder joints increased significantly, and the fracture mode of solder joints gradually changed from ductile fracture to brittle fracture. Among the three types of solder joints, the creep resistance of the hourglass-shaped solder joints is greatly affected by the thermoelectric coupling pretreatment.
Vector Field Segmentation With Normalized Cut

Given a set of points with associated velocity vectors, the goal is to partition a given data set into segments that capture the structure of the underlying two-dimensional (2D) field as defined by its critical points. The presented method models a vector field data as an undirected, weighted graph with the weights computed by a similarity measure that considers locally constructed linear least-squares approximations. A normalized-cut technique is used to partition a given data set into segments such that the vectors in each segment are highly correlated. For very large vector field data sets, we discuss a multilevel method that incorporates coarsening and refinement operations.
Do People Get Used to Insulting Language?

Verbal insults go against a universal moral imperative not to inflict harm on others, and they also pose a threat to one's face or reputation. As such, these “verbal slaps in the face” provide a unique opportunity to explore the interface between language and emotion. We used electroencephalography (EEG) and skin conductance (SC) recordings to compare the short-term impact of verbal insults such as “Linda is an idiot” or “Paula is horrible” to that of more positive evaluations (e.g., “Linda is an angel”, “Paula is impressive”) and neutral factual descriptions (e.g., “Linda is a student”), examining how responses to these various speech acts adapt as a function of massive repetition. By using either the participant's or somebody else's name, we also explored how statement impact depended on who was being evaluated. Multilevel ERP analysis with three predesignated latency ranges revealed an early insult effect in P2 amplitude that was highly robust over repetition and also did not depend on who the insult was about. This P2 effect points to a very rapid and stable capture of emotional attention, plausibly triggered by the retrieval of evaluative word meaning from long-term memory. Insults also elicited a larger late positive potential (LPP), again regardless of who the insult was about, but this later effect did not withstand repetition. Skin conductance responses showed that insults did not lead to more arousal than compliments did. In all, our findings suggest that in a standard psycholinguistic comprehension experiment without real interaction between speakers, insults deliver lexical “mini-slaps in the face,” such that the strongly negative evaluative words involved (e.g., “idiot”) automatically grab attention during lexical retrieval, regardless of how often that retrieval occurs.
Impact of Noise and Nonlinearity on Analog Self- Interference Cancellation in In-Band Full-Duplex Communications

Wireless revolution has evolved in ever-increasing demands on an already constrained wireless spectrum, driving the quest for increased bandwidths, greater channel capacity, and faster access rates. In-band full-duplexing (IBFD) is a promising technology that aims to answer this mitigation call by bolstering spectral efficiency through simultaneous same frequency band transmission and reception. However, transmitter-to-receiver leakage, or self-interference, remains the most barring frustration to IBFD realization. Therefore, self-interference cancellation (SIC) is necessary to suppress any polluting SI to a level below the receiver’s noise floor. The level of energy reduced by SIC determines the quality of the radio as well as overall system throughput. In this paper, a simulation model of an IBFD transceiver is developed in MATLAB, with inclusion of various sources of distortion. Subsequent results detailing an investigative study done on a fully adaptive tapped-branch analog self-interference canceller are shown. Evaluation of the results reveal marginal effect on the SIC efficacy due to transmission path noise and nonlinear distortion alone. However, expansion of model consideration for conceivable cancellation hardware nonlinearity reveals an indirectly proportional degradation of SIC performance by up to 35dB as distortion levels vary from −80dBm to −10dBm. These results indicate consideration of such nonidealities should be an integral part of cancellation hardware design for the preclusion of any intrinsic cancellation impediments.
The role of nutritional status in the relationship between diabetes and health-related quality of life

BACKGROUND/OBJECTIVES The association between nutritional status and health-related quality of life (HRQoL) among patients with type 2 diabetes mellitus (T2DM) is not fully understood. This study was conducted to understand the role of nutritional status on HRQoL among people with and without T2DM. SUBJECTS/METHODS Structured survey and direct measurement of anthropometric data were conducted among people with and without T2DM. Nutritional status was measured with Mini Nutritional Assessment tool and HRQoL was measured with a 36-item Short Form Healthy Survey. Data collection was conducted in Chuncheon, South Korea with 756 participants who are older than 40 yrs of age. RESULTS This study found that overall HRQoL were significantly lower in people with T2DM than people without T2DM after controlling for key covariates. When stratified by nutritional status, a greater degree of negative impact of T2DM on overall physical HRQoL was observed among well-nourished or at risk of malnutrition, whereas significant and more evident negative impact of diabetes on overall psychological HRQoL was observed only among malnourished. CONCLUSIONS The study results suggest the role of nutritional status among people with T2DM on overall, especially psychological aspects of HRQoL. Future longitudinal or intervention studies are warranted to test the impact of nutritional status on HRQoL among people with T2DM.
Characteristics of Fungal Communities and Internal Mildew Occurrence during the Stages of Planting and Storing of Sunflower Seed in China

Internally mildewed sunflower seeds pose a significant risk to human health. To control internal mildew, it is imperative to study its source in the main production area of China, which has been little investigated. Here, high-throughput sequencing was used to characterize the fungal and fungus-seed communities. Alpha diversity and ANOSIM analyses showed mildew did not alter the fungal compositions significantly. STAMP analysis showed that the sunflower seeds were most vulnerable to internal mildew during the field-planting stage. Alternaria was the predominant mildew-causing pathogen of sunflower seeds for consumption, which may originate from seed transmission and colonize at the seed-development stage. Finally, only a few seeds developed internal mildew with a worrisome level of Alternaria contamination in the humid field climate. NMDS analysis showed that climatic factors also played important roles in shaping microbial change during storage, with a relative humidity (RH) of 67% being the critical threshold in normal-temperature warehouses. Internal mildew never occurred below the RH threshold for the microbial community structure, which hardly changed after an average storage duration. The results indicated that a combination of field management to combat Alternaria, pretreatment with 5 KGy γ-irradiation and drying at the time of storage will minimize or prevent internal mildew. This work also provides an empirical framework for studies of mildewing in other shelled seeds.
A Hybrid FMCDM Approach for the Evaluation and Selection of Homestays

Due to the beautiful rural scenery, rural tourism has gradually become a popular trend as affected by urbanization in Taiwan. The purpose of this study is to develop an objective and systematic evaluation model for homestay selection in Taiwan. Specifically, this study combines three fuzzy multiple-criteria decision-making (FMCDM) methods of means-end chain (MEC), fuzzy decision making and trial evaluation laboratory (FDEMATEL), and fuzzy analytic hierarchy process (FAHP). First, we use MEC to obtain important factors for homestay travelers to choose homestays, then we extract key influencing factors by FDEMATEL method, and finally, we rank these factors in importance by FAHP to provide travelers and managers with a reference. In addition, this study combines fuzzy theory to avoid the bias caused by human subjective judgment, so as to solve the problem of objectivity in the selection and evaluation model of homestay criteria. According to the results of our case studies, a clean environment, professional service staff, safe facilities and beautiful buildings are the key factors for consumers to choose homestays. The results of this study can provide a reference for homestay managers to understand the priorities of travelers and optimize customer service in Taiwan.
Impact of ESG score on financial performance of Indian firms: static and dynamic panel regression analyses

ABSTRACT The study attempts to empirically investigate the impact of ESG score on the financial variables that may affect the performance of firms in the Indian context; SEBI’s recent mandate on ESG reporting by the listed entities being the point of departure for the present discourse. A representative sample of 48 Indian firms having ESG scores under BSE-100 index is used in the analysis. The study period comprises the years 2011–2019. Static and dynamic panel regression analyses are conducted. The financial performance variables incorporated in this paper include ROA, ROE, firm size, market capitalization, PBDIT, Tobin’s Q and share price. It is demonstrated that ESG score influences these variables, however with time lags. The distinctive contribution of the current endeavour lies in establishing a long-term positive association between ESG disclosure and annual average share price for the listed firms in a developing economy like India. The results are implicative of the fact that ESG score is an emerging indicator for conceiving future financial performance and risk mitigation strategies, and therefore, of considerable importance from policy perspective.
Citicoline Treatment in Acute Ischemic Stroke: A Randomized, Single-Blind TMS Study

Background Recent research on animal models of ischemic stroke supports the idea that pharmacological treatment potentially enhancing intrinsic brain plasticity could modulate acute brain damage, with improved functional recovery. One of these new drugs is citicoline, which could provide neurovascular protection and repair effects. Objectives The objective of this randomized, single-blind experimental study was to evaluate whether the treatment with Rischiaril® Forte was able to restore intracortical excitability measures, evaluated through transcranial magnetic stimulation (TMS) protocols, in patients with acute ischemic stroke. Methods Patients with acute ischemic stroke were recruited and assigned to an eight-week therapy of standard treatment (control group - CG) or CDP-choline (Rischiaril® Forte, containing 1,000 mg of citicoline sodium salt) added to conventional treatment (treatment group - TG). Each subject underwent a clinical evaluation and neurophysiological assessment using TMS, pretretament and posttreatment. Results A total of thirty participants (mean [SD] age, 68.1 [9.6] years; 11 women [37%]) completed the study. We did not observe significant changes in clinical scores after CDP-choline treatment (all p > 0.05), but we observed a significant improvement in short-interval intracortical inhibition (SAI) (p = 0.003) in the TG group compared to the CG group. Conclusions The eight-week treatment with citicoline after acute ischemic stroke may restore intracortical excitability measures, which partially depends on cholinergic transmission. This study extends current knowledge of the application of citicoline in acute ischemic stroke.
SARS-CoV-2 Amino Acid Mutations Detection in Greek Patients Infected in the First Wave of the Pandemic

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel virus that belongs to the Coronoviridae family, emerged in December 2019, causing the COVID-19 pandemic in March 2020. Unlike previous SARS and Middle East respiratory syndrome (MERS) outbreaks, this virus has a higher transmissibility rate, albeit a lower case fatality rate, which results in accumulation of a significant number of mutations and a faster evolution rate. Genomic studies on the mutation rate of the virus, as well as the identification of mutations that prevail and their impact on disease severity, are of great importance for pandemic surveillance and vaccine and drug development. Here, we aim to identify mutations on the SARS-CoV-2 viral genome and their effect on the proteins they are located in, in Greek patients infected in the first wave of the pandemic. To this end, we perform SARS-CoV-2 amplicon-based NGS sequencing on nasopharyngeal swab samples from Greek patients and bioinformatic analysis of the results. Although SARS-CoV-2 is considered genetically stable, we discover a variety of mutations on the viral genome. In detail, 18 mutations are detected in total on 10 SARS-CoV-2 isolates. The mutations are located on ORF1ab, S protein, M protein, ORF3a and ORF7a. Sixteen are also detected in patients from other regions around the world, and two are identified for the first time in the present study. Most of them result in amino acid substitutions. These substitutions are analyzed using computational tools, and the results indicate minor or major impact on the proteins’ structural stability, which could probably affect viral transmissibility and pathogenesis. The correlation of these variations with the viral load levels is examined, and their implication for disease severity and the biology of the virus are discussed.
Bird’s Nest Detection Algorithm for Transmission Lines Based on Deep Learning

The bird’s nest on the power transmission tower may cause the occurrence of bird flash accidents and threaten the safe and reliable operation of the power grid. The realization of the independent identification and positioning of the bird’s nest has always been a research hotspot. With the gradual deepening of the application of UAV inspection, higher requirements are put forward for the accuracy and speed of the bird’s nest recognition algorithm. This paper proposes a bird’s nest defect recognition method based on YOLOv5, which is composed of backbone network, FPN and YOLO head. After multiple rounds of training on the construction of the bird’s nest defect database and model of the transmission line, the independent identification and positioning of the bird’s nest has been realized. The results show that the recognition rate of the YOLOv5 model for the bird’s nest can reach 83.4%, and the FPS can reach 85.32. The recognition algorithm based on YOLOv5 proposed in this paper can meet the real-time and accuracy requirements of UAV inspection for target detection.
Resolving Continental Magma Reservoirs With 3D Surface Wave Tomography

Surface wave tomography is widely used to improve our understanding of continental magma reservoirs that may be capable of fueling explosive volcanic eruptions. However, traditional surface wave tomography based on inversions for phase velocity maps and locally 1D shear velocity may have difficulty resolving strong 3D low‐velocity anomalies associated with crustal magma reservoirs. Here, we perform synthetic tomography experiments based on 3D seismic waveform simulations to understand how the limitations of surface wave tomography could affect interpretations of tomography in volcanic settings. We focus our modeling on the Yellowstone volcanic system, one of the largest and most thoroughly studied continental magmatic systems, and explore scenarios in which the maximum shear velocity anomaly associated with the crustal magma reservoir ranges between −10% and −66%. We find that even with the well‐instrumented setting near Yellowstone, the recovered shear velocity anomalies in the mid‐to‐upper crust are severely diminished due to the small spatial scale of the reservoir with respect to the seismic wavelengths that sample it. In particular, recovered VS anomalies could be reduced by a factor of two or more, implying that the inferred melt fraction of large‐scale continental magma reservoirs may be considerably underestimated.
Estimating genotypic richness and proportion of identical multi-locus genotypes in aquatic microalgal populations

Abstract The majority of microalgal species reproduce asexually, yet population genetic studies rarely find identical multi-locus genotypes (MLG) in microalgal blooms. Instead, population genetic studies identify large genotypic diversity in most microalgal species. This paradox of frequent asexual reproduction but low number of identical genotypes hampers interpretations of microalgal genotypic diversity. We present a computer model for estimating, for the first time, the number of distinct MLGs by simulating microalgal population composition after defined exponential growth periods. The simulations highlighted the effects of initial genotypic diversity, sample size and intraspecific differences in growth rates on the probability of isolating identical genotypes. We estimated the genotypic richness for five natural microalgal species with available high-resolution population genetic data and monitoring-based growth rates, indicating 500 000 to 2 000 000 distinct genotypes for species with few observed clonal replicates (<5%). Furthermore, our simulations indicated high variability in genotypic richness over time and among microalgal species. Genotypic richness was also strongly impacted by intraspecific variability in growth rates. The probability of finding identical MLGs and sampling a representative fraction of genotypes decreased noticeably with smaller sample sizes, challenging the detection of differences in genotypic diversity with typical isolate numbers in the field.
Knowledge and risk assessment of depression among adolescents during the COVID-19 pandemic

Introduction: Depression, perceived in terms of a health problem, is a disorder that spreads dynamically in the youth population. The COVID-19 pandemic has exacerbated the problem. Aim: The aim of the study was to assess the level of knowledge and the risk of depression in the environment of a selected group of young people in the initial period of the COVID-19 pandemic. Material and methods: The study group consisted of 100 people - school students aged 15-20 years. An original questionnaire and the Kutcher Depression Scale for Youth were used. Results: The level of knowledge of adolescents about the risk factors for depression and symptoms that may indicate depression is average. Young people acquire knowledge from the Internet (41%) and TV programs (16%). Symptoms of depression were more frequent in: older participants of the study, those who assessed their financial situation as low, and students who had experience of depression in their family. The study revealed symptoms of depression in 22% of people. The severity of depression symptoms differed with age, self-esteem and family experience of depression. Conclusions: The obtained results constitute the basis for undertaking urgent preventive measures - both in the educational and psychotherapeutic sphere.
Driving pattern analysis of hybrid and electric vehicles in a German conurbation including a drive system evaluation

The official vehicle consumption data given by the vehicle manufacturer are in many countries based on standardised test cycles such as the New European Driving Cycle (NEDC). In reality, vehicle consumption normally differs depending on the individual usage profile. However, the knowledge of realistic consumption patterns plays an important role especially in the case of electric vehicles due to the range reduction due to energy consumption. This paper gives an overview of the typical usage profiles of electric and hybrid cars based on real driving data, which was recorded within a German conurbation. Based on these recorded driving profiles in combination with appropriate vehicle simulation models realistic consumption patterns and ranges are generated. Effects of different charging scenarios and various battery sizes are discussed. Finally, the suitability and efficiency of conventional cars as well as battery electric and plug-in hybrid electric vehicles for the regarded driving profiles are compared and evaluated.