Miracle-dz/UniFAR-FTUs huggingface dataset:
Speaking Corona? Human and Machine Recognition of COVID-19 from Voice

With the COVID-19 pandemic, several research teams have reported successful advances in automated recognition of COVID-19 by voice. Resulting voice-based screening tools for COVID-19 could support large-scale testing efforts. While capabilities of machines on this task are progressing, we approach the so far unexplored aspect whether human raters can distinguish COVID-19 positive and negative tested speakers from voice samples, and compare their performance to a machine learning baseline. To account for the challenging symptom similarity between COVID-19 and other respiratory diseases, we use a carefully balanced dataset of voice samples, in which COVID-19 positive and negative tested speakers are matched by their symptoms alongside COVID-19 negative speakers without symptoms. Both human raters and the machine struggle to reliably identify COVID-19 positive speakers in our dataset. These results indicate that particular attention should be paid to the distribution of symptoms across all speakers of a dataset when assessing the capabilities of existing systems. The identification of acoustic aspects of COVID-19-related symptom manifestations might be the key for a reliable voice-based COVID-19 detection in the future by both trained human raters and machine learning models. Copyright ©2021 ISCA.
Intrafamily relations and resilience as protectors against depressive symptoms in Mexican high school students

Introduction. Between 27.3% and 31.5% of adolescents in Mexico may present symptoms of depression. This issue has been studied from both family and resilience perspectives, although few studies have examined their interaction. Objective. In this study, we evaluated the influence of intrafamily relations and resilience on depressive symptoms in Mexican high school students, for which an analysis by sex was conducted. Method. For this correlation cross-sectional study, we evaluated 511 adolescents using the Revised Depression Scale of the Center for Epidemiological Studies, the short version of the Intrafamily Relation Evaluation Scale, and the Revised Resilience Questionnaire for Children and Adolescents. We performed multiple linear regression analyzes by sex using the stepwise method. Results. For young men, the predictor variables were expression, difficulties, and problem-solving (R2a = .34), whereas for young women the variables were union and support, difficulties, and empathy (R2a = .25). Discussion and conclusion. This study indicates specific aspects of intrafamily relations and resilience to develop sex-sensitive interventions to prevent depression in high school students.
Evaluation of the anti-microbial properties of prepared herbal solution on dental impressions with irreversible hydrocolloid- an ex vivo study

Aim: of this study is evaluation of the anti-microbial properties of prepared herbal solution on dental impressions with irreversible hydrocolloid. The study is an ex-vivo comparative study. Material and methods: includes Herbal ingredients: Neem, Tulsi, Reetha, Aloe vera, Neem seed oil, Ginger oil, Peppermint oil, Gum acacia, and Rock salt were used to prepare herbal disinfectant solution. Preparation of this disinfectant solution includes extract preparation by reflux method, filtration, evaporation and homogenization. Minimum inhibitory concentration of this solution was determined and in-vitro antimicrobial properties were checked with disc diffusion method. To check whether the antimicrobial property of herbal solution was useful in dentistry, 10 sectional maxillary impressions of left side were made with irreversible hydrocolloid. In the molar area each impression was cut in two halves. One half was washed with water and other half was sprayed with herbal solution. Impressions were kept for 2 to 3 minutes and then placed in inoculated agar plates. Incubation of agar plates was done for 24 hours and checked for bacterial growth. Mann Whitney ‘U’ test and Chi Square test were used to evaluate the data. Results: found that Agar plates having sectioned alginate impression sprayed with disinfectant herbal solution showed less bacterial growth compared with the agar plates having alginate washed with water. To conclude Herbal disinfectant solution is effective in controlling the bacterial growth on impressions with irreversible hydrocolloid.
Multi-Task Neural Network for Robust Multiple Speaker Embedding Extraction

This paper introduces a novel approach for extracting speaker embeddings from audio mixtures of multiple overlapping voices. This approach is based on a multi-task neural network. The network ﬁrst extracts a latent feature for each direction. This feature is used for detecting sound sources as well as identifying speakers. In contrast to traditional approaches, the proposed method does not rely on explicit sound source separation. The neural network model learns from data to extract the most suitable features of the sounds at different directions. The experiments using audio recordings of overlapping sound sources show that the proposed approach outperforms a beamforming-based traditional method.
Biosynthesis, Characterization, Radical Scavenging and Antimicrobial Properties of Psidium guajava Linn Coated Silver and Iron Oxide Nanoparticles

The present research describes a rapid, green, and convenient method for bio-stimulated preparation of silver and iron oxide nanoparticles using the aqueous leaf extract of Psidium guajava Linn (PG). The physicochemical properties of bio-synthesized nanoparticles were determined through UV/Visible, SEM, EDX, and FTIR spectroscopic techniques. The wavelength maxima (nm) at 435 and 300 depict silver and iron oxide nanoparticles' formation, respectively. Scanning electron microscopic analysis infers the spherically shaped silver (81.4-102 nm) and iron oxide (80.3-99.1 nm) particles. The energy dispersive X-ray technique accomplished elemental mapping. The in vitro antioxidant properties of silver and iron oxide nanoparticles were assessed using 1,1-diphenyl-2-picryl-hydrazil (DPPH) radical method with IC50 values of 85.39±0.28 and 78.6±0.63, respectively. The antimicrobial potential was evaluated against selected Gram-positive and Gram-negative bacterial and fungal strains by the agar well diffusion method. The significant zone of inhibition against microbial pathogens reveals the potential industrial and biomedical applications of obtained nanoparticles. The antimicrobial prospective of guava extract-coated iron oxide nanoparticles has been studied for the first time against Bacillus pumilus, Streptococcus faecalis, Streptococcus pneumoniae, and Candida albican. The current report envisions the comparative evaluation of these nanoparticles' antimicrobial and antioxidant characteristics for the first time from this plant.
Systemic infection

In antiquity, transmission of disease was attributed to the miasma or contagion theory. In the Middle Ages, living in proximity to domestic animals and flies, the scarce use of soap, and absent sewage augmented the exposure to bacteria. In the early 19th century, Gordon, Holmes, and Semmelweis understood that maternal childbed fever—closely related to neonatal sepsis—was transferred by the physician’s hands to the mother during delivery. Before bacteria were discovered in the mid-19th century, septic infections in the newborn were perceived as different disorders: erysipelas, Buhl’s disease, Winckel’s disease, and so on. With the advent of microbiology, sepsis became heterogeneous and was mainly defined by the causing microorganism. In the 1940s, group B streptococci emerged as a pathogen of newborns and soon became the commonest cause of neonatal sepsis. The discovery of antibiotics made the deadly disease treatable. In the 1970s, resistant bacterial strains emerged and allied dangerously with indwelling devices, especially central venous catheters. In the developing world, neonatal sepsis remains a major cause of infant mortality.
51 Flavors: Regional Resource Configurations and Foreign Multinational Market Entry in the U.S. Biopharmaceutical Industry

Creating a sustainable regional economy requires not only attracting new local ventures, but also foreign multinationals. In this regard, understanding which resources are influential in market entry decisions is crucial given that there are different resource needs between developed (DMNE) and emerging market (EMNE) multinationals. Answering calls for more neo-configurational studies in the literature, our study uses a fuzzy-set qualitative comparative analysis (fsQCA) approach to examine foreign multinational entry decisions in 51 regions of the U.S. We constructed a novel dataset comprised of 3287 foreign firms from 61 countries and territories operating in the biopharmaceutical industry. We find that there are substantial differences in the configuration of resources that attract DMNEs and EMNEs to regions. The resource configurations in our models account for over 80% of the factors influencing DMNE and EMNE market entry location decisions. Some resources played a more important role in these decisions, such as FDI stocks, cluster size, and manufacturing intensity. Our findings show that EMNEs seek out regions with a greater abundance of different resources than DMNEs. This study provides practical implications for firms entering foreign markets as well as for policy makers who want to attract these firms to bolster their regional economic development.
Stacked Recurrent Neural Networks for Speech-Based Inference of Attachment Condition in School Age Children

In Attachment Theory, children that have a positive perception of their parents are said to be secure, while the others are said to be insecure. Once adult, unless identiﬁed and supported early enough, insecure children have higher chances to experience major issues (e.g., suicidal tendencies and antisocial behavior). For this reason, this article proposes a speech-based automatic approach for the recognition of attachment in school-age children. The experiments are based on stacked RNNs and have involved 104 children of age between 5 and 9. The accuracy is up to 68.9% (F1 59.6%), meaning that the approach makes the right decision two times out of three, on average. To the best of our knowledge, this is the ﬁrst work aimed at inferring attachment from speech in school-age children.
The approaches for localized surface plasmon resonance wavelength position tuning. Short review

A unique feature of nanoparticles made from highly conductive materials (plasmonic nanoparticles) is that their localized surface plasmon resonance (LSPR) wavelength position can be tuned by changing the shape, size, composition and environment in accordance with the purpose of the application. In this paper, the main mechanisms of LSPR tuning that are available at the present time are reviewed. In particular, a widely used method for tuning the LSPR wavelength position is based on selecting the type of a plasmonic nanoparticle material such as gold, silver, copper, aluminum and gold-silver alloy. The examples of changing the resonance absorption position by using nanoparticles with different shapes and dimensions have been аlso demonstrated. Furthermore, works with less used LSPR tuning methods, such as controlled regulation of the distance between nanoparticles in one and two dimensions have been considered. The number of works is given, where the LSPR wavelength position can be also controlled by changing the environment in the vicinity of plasmonic nanoparticle: the substrate thickness, the thickness and dielectric parameters of the layer on the surface of the nanoparticle. Examples of active influence on the change in the wave position of LSPR by applying an electric potential and regulating plasma modes have been also discussed.
Score-Driven Modeling of Spatio-Temporal Data

Abstract A simultaneous autoregressive score-driven model with autoregressive disturbances is developed for spatio-temporal data that may exhibit heavy tails. The model specification rests on a signal plus noise decomposition of a spatially filtered process, where the signal can be approximated by a nonlinear function of the past variables and a set of explanatory variables, while the noise follows a multivariate Student-t distribution. The key feature of the model is that the dynamics of the space-time varying signal are driven by the score of the conditional likelihood function. When the distribution is heavy-tailed, the score provides a robust update of the space-time varying location. Consistency and asymptotic normality of maximum likelihood estimators are derived along with the stochastic properties of the model. The motivating application of the proposed model comes from brain scans recorded through functional magnetic resonance imaging when subjects are at rest and not expected to react to any controlled stimulus. We identify spontaneous activations in brain regions as extreme values of a possibly heavy-tailed distribution, by accounting for spatial and temporal dependence.
Critical coupling span number in high-speed railway simply supported beam bridge

In long-distance railways, some particular spans of high-speed railway simply supported beam bridges (HSRSBs) are commonly selected as the target structure. The target structure is the part of interest for the study and intended to be analyzed. Due to longitudinal constraints of the track system, the target structure is tightly coupled with other spans within certain range, and is affected by the coupled spans under longitudinal earthquake condition. A massive amount of time-consuming computation is required to determine the coupling span number using current finite element models. In an effort to overcome this challenge, an equivalent method for the longitudinal constraints of the track system is proposed, which greatly reduces the complexity of finite element model while retaining calculation precision. The coupling span number was determined by seismic analyses of a large number of cases using equivalent finite element models. Moreover, the influence of pier height and bottom pier stiffness on coupling span number was studied. Based on the relationship between the equivalent boundary sensitivity critical point and coupling span number, a method to quickly obtain coupling span number of the target structure in arbitrary HSRSB was constructed.
Masters & Johnson – their unique contribution to sexology

SUMMARY The scientific study of human sexuality is now accepted as mainstream practice but early researchers in the field often attracted considerable criticism. Masters and Johnson were pioneers in observing and describing normal sexual function and consequently they provided unique insights into helping to understand sexual dysfunction. Their contribution to describing the physiological process of sexual response alongside potential psychological factors resulting in and maintaining sexual dysfunction is widely acknowledged. Their work continues to influence contemporary sexual medicine and psychosexual therapeutic practice.
Robust facility layout design for flexible manufacturing: a doe-based heuristic

Flexible manufacturing systems (FMS) should be able to respond to changing manufacturing requirements and environments. From the layout point of view, FMS need to be rearranged to fit the new requirements. However, rearranging the layout is often undesirable due to its unpredicted high costs and production disruption. This paper proposes a practical approach to mitigate the effects and repercussions of changing environments and avoid rearranging the layout. A robust layout approach is presented, where changes in product demand and mix are absorbed by altering product routes and not rearranging the layout. In this approach, the problem is decomposed into two sub-problems: sub-problem 1 (SP1) where a robust layout is constructed, and sub-problem 2 (SP2) to obtain the best routes of products. To solve SP1, design of experiments is used to find a critical period, which is the period most affected under demand changes. Then, the layout for the critical period is determined using a hybridized genetic-tabu search algorithm. Then SP2 is solved by a branch and cut algorithm to obtain the optimal routes of the products in each period. The performance of the proposed methodology is illustrated using a case study and is benchmarked against rival ones from the literature.
The extractive embrace: shifting expectations of conservation and extraction in the Guiana Shield

ABSTRACT This paper demonstrates what the Reducing Emissions from Deforestation and forest Degradation (REDD+) initiative would have to do to satisfy the expectations of its diverse, local stakeholders. It connects the unmet expectations of REDD+ with a deepening reliance on extractive activity in the Guiana Shield. In it, I argue that extractive activity, which has always been the most significant driver of deforestation in the ecoregion, is further overtaking REDD+’s capacity for meeting expectations and development aspirations due to the combined failure of REDD+ to deliver vast amounts of promised funding to alter unsustainable development paths and the subsequent announcements of major oil discoveries in the territorial waters of the Guiana Shield. These arguments are based on data collected in the early phases of REDD+ readiness through a multi-sited ethnography, analyzed through a combination of Foucauldian discourse analysis and governmentality. I use critical discourse analysis to represent REDD+’s regional interpretations and governmentality to tease out the expectations embedded in these discourses. This combination supports my identification of what REDD+ would have to accomplish to be deemed successful in Guyana and Suriname, the only two REDD+ participating countries entirely within the Guiana Shield. In turn, this identification improves understandings of the relationship between failed or failing conservation and development initiatives and the subsequent intensification of extractive activity.
Bacillus subtilis (Bacillales, Bacillaceae) Spores Affect Survival and Population Growth in the Grain Aphid Sitobion avenae (Hemiptera, Aphididae) in Relation to the Presence of the Facultative Bacterial Endosymbiont Regiella insecticola (Enterobacteriales, Enterobacteriaceae)

Abstract The grain aphid Sitobion avenae (Fabricius) is one of the most important cereal pests, damaging crops through sap sucking and virus transmission. Sitobion avenae harbors the secondary endosymbiont Regiella insecticola, which is highly prevalent in populations in south-central Chile and other regions of the world. In order to develop ecological alternatives for biological control, we studied the effect of applying the spores of a strain of the bacterium Bacillus subtilis on the survival and fecundity of the most prevalent genotype of S. avenae in central Chile. The strain selected was one that in previous studies had shown the ability to outcompete other bacteria. Using clones of this aphid genotype infected and uninfected with R. insecticola, we found that applying B. subtilis spores through artificial diets and spraying on leaves decreased both adult survival and nymph production. The detection of spores within the aphid body was negatively correlated with nymph production and was lower in the presence of R. insecticola when applied in diets. B. subtilis spores applied on leaves reduced the number of aphids, an effect that was stronger on aphids harboring R. insecticola. A possible interaction between endosymbiotic bacteria and bacterial antagonists within the aphid body is discussed.
On Microservice Analysis and Architecture Evolution: A Systematic Mapping Study

Microservice architecture has become the leading design for cloud-native systems. The highly decentralized approach to software development consists of relatively independent services, which provides benefits such as faster deployment cycles, better scalability, and good separation of concerns among services. With this new architecture, one can naturally expect a broad range of advancements and simplifications over legacy systems. However, microservice system design remains challenging, as it is still difficult for engineers to understand the system module boundaries. Thus, understanding and explaining the microservice systems might not be as easy as initially thought. This study aims to classify recently published approaches and techniques to analyze microservice systems. It also looks at the evolutionary perspective of such systems and their analysis. Furthermore, the identified approaches target various challenges and goals, which this study analyzed. Thus, it provides the reader with a roadmap to the discipline, tools, techniques, and open challenges for future work. It provides a guide towards choices when aiming for analyzing cloud-native systems. The results indicate five analytical approaches commonly used in the literature, possibly in combination, towards problems classified into seven categories.
Relationship between phenology and frost damage to female strobili of pine wood nematode-resistant clones of Japanese black pine (Pinus thunbergii): a case study in an experimental crossing garden during the spring of 2020

ABSTRACT To clarify the factors affecting the level of spring frost damage in seed orchards of pine wood nematode (PWN)-resistant Pinus thunbergii, we investigated the frost damage to the female strobili of 13 PWN-resistant P. thunbergii clones in an experimental crossing garden during the spring of 2020. Monthly air temperatures from January to March 2020 were higher than the corresponding temperatures in the previous six years, whereas the temperatures in April 2020 were lower compared to the previous years. The number of female strobili on the upper and lower branches of the trees averaged 4.7 and 2.7, respectively. The spring frost damaged 6% and 22% of the strobili on the upper and lower branches, respectively. A generalized linear mixed model analysis confirmed that this difference was significant; moreover, it showed significant clonal variation in the female strobili mortality. The mortality risk to the female strobili of each clone was negatively correlated to the time required for the female strobili to bloom. Thus, the P. thunbergii clones with an early flowering phenology are more likely to suffer from spring frost damage.
CPT-TODIM METHOD FOR INTERVAL-VALUED BIPOLAR FUZZY MULTIPLE ATTRIBUTE GROUP DECISION MAKING AND APPLICATION TO INDUSTRIAL CONTROL SECURITY SERVICE PROVIDER SELECTION

In recent years, a series of serious attacks against industrial control system (ICS), such as Stuxnet, Duqu, Flame and Havex, have sounded the alarm for industrial enterprises. For many industrial enterprises, it is a very important part of enterprise management decisions to evaluate ICS security suppliers and choose the appropriate one as a partner. The purpose of this paper is to build the TODIM method based on cumulative prospect theory (CPT-TODIM) to solve multiattribute group decision making problem under interval-valued bipolar fuzzy environment. This extraordinary model not only uses CPT to supplement the traditional TODIM method, but also introduces the entropy weight method to determine the attribute weight so as to avoid the negative influence of subjective weight on the decision result. In addition, in this model, all attribute evaluation information will be interval-valued bipolar fuzzy number (IVBFN) to cope with complex and fuzzy decision environment. Then, the most important part of this paper, we elaborate on the logical structure of the model. What’s more, in the last two sections, we apply this newly constructed model to the selection of ICS security suppliers, and verify the acceptability of this method by sensitivity analysis and comparing with IVBFWA and IVBFWG operator.