Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross-Linguistic Perception of the Japanese Singleton/Geminate Contrast: Korean, Mandarin and Mongolian Compared

The perception of Japanese consonant length contrasts (i.e. short/singleton vs long/geminate) by native and non-native speakers was compared to examine the extent to which difficult foreign language (FL) sounds are processed accurately. Three groups of participants had Korean, Mandarin or Mongolian as their first language (L1) and had no experience with Japanese. Unlike Japanese, Mandarin and Mongolian do not use consonant length contrastively. The phonemic status of consonant length in Korean is debatable. Further, unlike Japanese and Mandarin which predominantly use open syllables and restrict the occurrence of consonants in coda position, Korean and Mongolian permit a wide range of consonants in that syllable position. Via the AXB task, the participants’ discrimination accuracy of Japanese consonant length contrasts was assessed and compared to that of a group of 10 native Japanese speakers who served as controls. The Japanese group was at near ceiling with little individual variation. The Mongolian (but not Korean and Mandarin) group did not significantly differ from the control group when the target token (X) contained a geminate. All non-native groups were significantly less accurate than the control group when X contained a singleton. These results were interpreted as reflecting the participants’ L1 quantity system.
Molecular identification and phylogenetics of local pearl millet cultivars using internal-transcribed spacers of nuclear ribosomal DNA

Local cultivars of pearl millet in Saudi Arabia are known to tolerate extreme heat and drought stress. In the current study, the sequences of internal-transcribed spacers (ITSs) of six pearl millet cultivars were sequenced and analysed to investigate the genetic diversity among the local cultivars. The nucleotide polymorphism, secondary structures and phylogenetics were analysed for ITS sequences of the six local cultivars. The obtained sequences were 772–774 base pairs (bp) in length, including complete sequences of the ITS1–5.8S–ITS2 region and partial sequences of 18S and 26S rRNA. The nucleotide diversity among cultivars was higher in ITS2 sequences than ITS1 sequences. The ITS2 had four variable nucleotide sites in three native cultivars, whereas the ITS1 contained one base insertion. The secondary structures of the ITS1 and 5.8S region were highly conserved among the six cultivars and contained some motifs that are conserved across Viridiplantae. However, the ITS2 secondary structure for the two native cultivars, Sayah and Jazan, was distinct from the other cultivars, which confirms the applicability of the ITS2 sequence in distinguishing between genetically close taxa. Additionally, the phylogenetic analysis of the six investigated cultivars and 31 pearl millet accessions from the NCBI database showed close relationships between the local accessions and NCBI accessions from India and France. However, the local cultivar Sayah appeared to be distinct from the other cultivars in the phylogenetic trees. This study provides insights into the polymorphism within local pearl millet cultivars which is important for the identification and conservation of these cultivars.
Learning Time Acceleration in Support Vector Regression: A Case Study in Educational Data Mining

The development of a country involves directly investing in the education of its citizens. Learning analytics/educational data mining (LA/EDM) allows access to big observational structured/unstructured data captured from educational settings and relies mostly on machine learning algorithms to extract useful information. Support vector regression (SVR) is a supervised statistical learning approach that allows modelling and predicts the performance tendency of students to direct strategic plans for the development of high-quality education. In Brazil, performance can be evaluated at the national level using the average grades of a student on their National High School Exams (ENEMs) based on their socioeconomic information and school records. In this paper, we focus on increasing the computational efficiency of SVR applied to ENEM for online requisitions. The results are based on an analysis of a massive data set composed of more than five million observations, and they also indicate computational learning time savings of more than 90%, as well as providing a prediction of performance that is compatible with traditional modeling.
Cross-Lingual Speaker Adaptation Using Domain Adaptation and Speaker Consistency Loss for Text-To-Speech Synthesis

We present a cross-lingual speaker adaptation method based on domain adaptation and a speaker consistency loss for text-to-speech (TTS) synthesis. Existing monolingual speaker adaptation methods based on direct ﬁne-tuning are not applicable for cross-lingual data. The proposed method ﬁrst trains a language-independent speaker encoder by speaker veriﬁcation using domain adaption on multilingual data, including the source and the target languages. Then the proposed method trains a monolingual multi-speaker TTS model on the source language’s data us-ing the speaker embeddings generated by the speaker encoder. To adapt the TTS model of the source language to new speakers the proposed method uses a speaker consistency loss to maximize the cosine similarity between speaker embeddings generated from the natural speech and the same speaker’s synthesized speech. This makes ﬁne-tuning the TTS model of source language on speech data of target language become possible. We conduct experiments on multi-speaker English and Japanese datasets with 207 speakers in total. Results of comprehensive experiments demonstrate that the proposed method can significantly improve speech naturalness compared to the baseline method.
Effects of Etanercept on Clinical and Immunological outcomes in Iraqi Patients with Rheumatoid Arthritis

Background: Rheumatoid Arthritis is a chronic autoimmune disease affects joints and connective tissueswhere different types of cytokines are involved in its pathogenesis and progression. Biological drugs areconsidered to be a more targeted treatments for rheumatoid arthritis. Therefore, the aim of current studywas to explore the effects of etanercept, a biological drug that inhibits tumor necrosis-alpha, on clinical andimmunological variables in Iraqi patients with RA. Methods: A prospective open-label study conductedfrom February to November/ 2020 at Rheumatology Unit, Baghdad Teaching Hospital/ Medical city, Iraq.The study involved 75 patients with rheumatoid arthritis who underwent a 12-week course of treatment withetanercept monotherapy or combined with methotrexate. Assessments of disease activity and immunologicalmarkers (using SDAI and ELISA technique, respectively) were performed for the patients after the course oftreatment and compared with healthy controls. Results: Data from current study showed that disease activitywas not affected by type of treatment and immunological markers were higher in patients with rheumatoidarthritis than in control subjects regardless of type of treatment. Conclusion: To achieve an effectivecontrol of rheumatoid arthritis disease activity, treatment with etanercept (monotherapy or combined withmethotrexate) needs to be continued for more 12 weeks.
Predictive models with end user preference

Classical machine learning models typically try to optimize the model based on the most discriminatory features of the data; however, they do not usually account for end user preferences. In certain applications, this can be a serious issue as models not aware of user preferences could become costly, untrustworthy, or privacy‐intrusive to use, thus becoming irrelevant and/or uninterpretable. Ideally, end users with domain knowledge could propose preferable features that the predictive model could then take into account. In this paper, we propose a generic modeling method that respects end user preferences via a relative ranking system to express multi‐criteria preferences and a regularization term in the model's objective function to incorporate the ranked preferences. In a more generic perspective, this method is able to plug user preferences into existing predictive models without creating completely new ones. We implement this method in the context of decision trees and are able to achieve a comparable classification accuracy while reducing the use of undesirable features.
Estrogen on Candida spp. of the vagina: Is there any effect?

A variety of Candida spp. as the most common fungi in the human body can normally be found in the vagina competing with other microbotes. Their presence is influenced by a variety of conditions in the vaginal environment. The proliferation of Candida spp. in the vagina under specific conditions can result in a fungal disease known as vaginal candidiasis. More than 17 species of Candida out of 200 members of this genus are capable of causing diseases within the human body. Estrogen, along with other steroidal hormones, has been shown to have direct multifunctional effects on various pathogenic microorganisms by numerous activities. Its production as well as other factors such as disturbance of microbial balance and immune activity may alter the vaginal physical environment and promote the development of vaginal fungal infection. The vaginal functions can be affected by the level of circulation of estrogens in the blood according to the stage of the menstrual cycle in women. It also has many other functional actions on the vaginal structure. Estrogen and several other factors play an important role in determining the vaginal content of Candida species. Its effect could be a direct action on the cells of Candida or through an indirect effect on the immunity defenses of the vagina.
Pengaruh employee stock option plan (ESOP) terhadap earnings management (studi pada perusahaan yang listed di bursa efek indonesia periode 2015 – 2017)

This Study aimed to determine the effect of ESOP on Earnings Management. The populations of this study were all companies listed on the Indonesia Stock Exchange for the period 2015-2017. The sample was determined by purposive sampling technique and obtained 30 company’s annual reports as the sample. The data collection method used secondary data documentation techniques that was obtained from the website www.idx. co.id. Data analysis was performed using panel data regression analysis. The results showed that the ESOP had no effect on Earnings Management. Penelitian ini bertujuan untuk mengetahui pengaruh ESOP terhadap Earnings Management. Populasi penelitian ini seluruh perusahaan yang terdaftar di Bursa Efek Indonesia periode 2015-2017. Sampel ditentukan dengan teknik purposive sampling dan diperoleh sampel 30 laporan tahunan perusahaan. Teknik pengumpulan data menggunakan teknik dokumentasi data sekunder yang diperoleh dari website www.idx. co.id. Analisis data menggunakan analisis regresi data panel. Hasil penelitian menunjukkan ESOP tidak berpengaruh terhadap Earnings Management.
Event-triggered control of vehicle platoon under deception attacks

This paper addresses the issue of control of a vehicle platoon system with limited on-board energy and communication resources and subjected to cyber-physical attacks. A platoon model for the predecessor-leader following topology under the effect of cyber-attack and time-varying delay is developed. A stochastic type deception attack is considered in this paper at the sensor-controller end of a vehicle. The probability of occurrence of attack is represented using a random variable. In addition, to reduce the usage of resources in a system, a decentralized event-triggering communication mechanism is proposed where each vehicle can decide independently on when to transmit its state to the controller. Further, the criteria for co-designing of control law and triggering parameter ensuring internal stability of the platoon system is developed based on the proposed triggering mechanism. A condition to achieve string stability for the controller is also obtained. Further, to avoid the problem of Zeno phenomena, a lower bound on the transmission period is presented. The effectiveness of the proposed methodology is established through simulation example.
Ichthyofauna of the Água das Araras stream, Paranapanema River basin, upper Paraná River system, Southern Brazil

ABSTRACT This study comprises the first fish inventory of the Água das Araras stream, a small tributary of the Laranjinha River, in the upper Paraná River basin. Four samplings were carried out seasonally between June 2010 and July 2011, in 12 collecting sites distributed from the headwater to the mouth of Água das Araras stream and its tributaries, using seines and gill nets to capture specimens. A total of 5,328 specimens were collected, distributed in six orders, 15 families, 33 genera, and 41 species. The most representative orders, in terms of species richness, were Siluriformes and Characiformes. Among the families, Characidae (eight species) and Loricariidae (seven species) presented higher richness contributing together with approximately 36.6% of all collected species. The most frequent species captured in ≥75% of the sampled sites were Astyanax lacustris, Characidium aff. zebra, Corydoras aeneus, and Imparfinis schubarti. The classification of species with the Kendeigh Index highlighted the following ranking of the more abundant species: Phalloceros harpagos, C. aeneus, A. lacustris, and I. schubarti. Finally, our results emphasize the importance of sampling small aquatic bodies, revealing their potential for maintaining a significant portion of fish diversity in Neotropical freshwater environments.
Privacy Concerns in Personalized Advertising Effectiveness on Social Media

One of the characteristics of industry 4.0 is that consumers increasingly want products to be made just for themselves. This can be supported by the presence of big data, which of course cannot be separated from the use of information, the more complete the data, the more precise and accurate the targeting will be. However, the use of information for some people can also be considered a violation of privacy. Various research about personalized advertising been tested and have yielded mixed results both positive and negative on perceptions and behaviour, and provide directions for next research to testing various consumer factors as moderating variable. This study aims to fill the gaps in previous research by examining the role of consumer privacy concerns as a moderating variable that affects the relationship of personalized advertising on the perceived advertising value of consumers using a survey method on 131 respondents who are active users of Instagram in Indonesia. The findings of this study that advertising personalization have a positive effect on advertising value and purchase intention and privacy concerns do not moderate the effect of personalized advertising on advertising value. This is influenced by the factor of respondents aged 17-25 years, where they can be said to be the Tech Savvy generation. Further research suggestions are also discussed in this study.
Drug repurposing combined with MM/PBSA based validation strategies towards MEK inhibitors screening

Abstract Emergence of oncogenic mutations in the MAPK pathway gaining more impact in the recent years. Importantly, MEK is a core element of this pathway as it is easy to inhibit and is a gatekeeper of multiple malignancies. Therefore, we performed in-silico strategy to screen repurposed candidate for MEK protein using a library of 11,808 compounds from different clusters in the DrugBank database. Glide docking, Prime-MM/GBSA and QikProp analysis were implemented to retrieve the hits with high precision. The stability of the binding mode and binding affinity of the resultant hit were explored using molecular dynamic simulations and MM/PBSA approach. The results highlight that Nebivolol (DB04861) not only achieved a stable conformation in the MEK binding pocket but also displayed highest binding affinity than the other molecules investigated in our study. Taken together, we hypothesized that Nebivolol is an excellent candidate for the inhibition of MEK in NSCLC patients in future. Communicated by Ramaswamy H. Sarma
Smart Architectural and Urban Heritage: An Applied Reflection

The aim of this paper is to present the use of 3D models and augmented reality (AR) to study and communicate architectural and urban values and, therefore, favor the development of dedicated forms of “smart heritage”. The study rises from a reflection on the concept of “heritage”, as defined in the international documents, intended as an evolving idea that puts together tangible and intangible aspects. Moreover, digital technologies favor “phygital” applications where the digital dimension support the traditional ones. In this way, AR allows the superimposition of multimedia information to heritage, respecting the historical matter of the artefacts, and supporting a “smart heritage” application. In particular, mobile AR, with real-time and ubiquitous visualizations, offers the opportunity to show past urban and architectural configurations to investigate and describe the transformations that have led to the current configuration, and consequently highlighting the present historical and architectural values of the buildings. Two case studies are presented: the square of St. Basilio Monastery, with its historical transformations, and the Basilica of Collemaggio, a pivotal building in the rites of “Perdonanza Celestiniana”.
Segment and Tone Production in Continuous Speech of Hearing and Hearing-Impaired Children

Verbal communication in daily use is conducted in the form of continuous speech that theoretically is the ideal data format for assessing oral language ability in educational and clinical domains. But as phonetic reduction and particularly lexical tones in Chinese are greatly affected by discourse context, it is a challenging task for automatic systems to evaluate continuous speech only by acoustic features. This study analyzed repetitive and storytelling speech produced by selected Chinese-speaking hearing and hearing-impaired children with distinctively high and low speech intelligibility levels. Word-based reduction types are derived by phonological properties that characterize contraction degrees of automatically generated surface forms of disyllabic words. F0-based tonal contours are visualized using the centroid-nearest data points in the major clusters computed for tonal syllables. Our results show that primary speech characteristics across different groups of children can be differentiated by means of reduction type and tone production.
Cisplatin Increased the Expression of PD-1 and PD-L1 by YAP1 in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) was one of the most malignant cancers in the world. Cisplatin (DDP) was one of the main chemotherapy drugs for HCC, but the mechanism of DDP treatment for HCC remains unclear. In this presentation, we found that DDP inhibited the growth of HCC cells and promoted the expression of PD-1 and its ligand PD-L1 in cancer cells. Meanwhile, flow cytometry analysis revealed that DDP enhanced PD-1-CD8+ T cells expression and decreased PD-1+CD8+ T cells expression. ELISA analysis suggested that DDP decreased TGF-β expression in vivo. Therefore, the study indicated that DDP enhanced PD-1 and PD-L1 expression and inhibited the growth of HCC.
Ordos Block (Basin) is a key to understand early continental evolution and tectonic regime of the North China Craton

The Ordos Block is one of the key elements of the North China Craton (NCC), and the Precambrian compositions and structures record the early-stage evolution of the NCC, such as cratonization of early continental crust, Paleoproterozoic mobile belts, Meso- and Neoproterozoic rifting, and platform development. Many basic issues on the early-stage tectonic evolution bear upon the Ordos Block. The following are some new achievements in fundamental geology of the Ordos Block. (1) Drill cores reveal that the Ordos Block possesses Neoarchean-Paleoproterozoic metamorphic basement. The Neoarchean granitic gneisses and Paleoproterozoic pelitic gneisses and granites of the Ordos Block are quite similar in geochemistry and metamorphism to the Paleoproterozoic metamorphic complexes and migmatite of the central and northern portions of the NCC. (2) The proto-Ordos Basin is an intra-cratonic basin with old crystalline basements. Precambrian sedimentary successions are mostly made with the Changcheng and Jixian systems, with the Qingbaikou and Nahua systems being largely absent. The Sinian or Ediacaran strata are partially preserved. The Paleozoic sequence of the Ordos Block is consistent with that of the rest parts of the NCC. (3) A Greater Ordos Basin existed in the Late Triassic, which extended eastward to the Bohai Gulf and Xuhuai belt. Precambrian basement rocks of the Lüliang and Taihang mountains were exhumed due to the NW-SE crustal shortening in the Mid-Late Jurassic, leading to the disruption of the Greater Ordos Basin. The Ordos Basin in a narrow sense was formed largely since the Late Jurassic. (4) The Ordos Basin proper is now surrounded by major active faults. Precambrian metamorphic rocks, which outcrop discontinuously beside the major faults, are compatible well with their counterparts in the other parts of the NCC in many respects like geochronology, geochemistry, and metamorphism. (5) The Ordos Block was in an extensional setting during Cretaceous and Cenozoic times, as manifested by rift basins, such as the Early Cretaceous rift zone in the western Ordos Basin and the Tertiary Shanxi, Weihe and Yinchuan grabens. The Lüliang and Taihang mountains were further uplifted as a result of crustal stretching. Recent studies confirm that the Ordos Block and the other parts of the NCC share the identical metamorphic basement and Mesoproterozoic-Paleozoic sedimentary sequences. Therefore, reconstructing tectonic history of the NCC should be based on careful analysis and logical explanation of geologic data as well as the reevaluation of some long-held conceptions. There have remained a number of disputes on how the North China continent originated and evolved. The Ordos Block can serve as an archive for solving the crux of the problems.
Non-Intrusive Speech Quality Assessment with Transfer Learning and Subject-Specific Scaling

In communication systems, it is crucial to estimate the perceived quality of audio and speech. The industrial standards for many years have been PESQ, 3QUEST, and POLQA, which are intrusive methods. This restricts the possibilities of using these metrics in real-world conditions, where we might not have access to the clean reference signal. In this work, we develop a new non-intrusive metric based on crowd-sourced data. We build a new speech dataset by combining publicly available speech, noises, and reverberations. Then we follow the ITU P.808 recommendation to label the dataset with mean opinion scores (MOS). Finally, we train a deep neural network to estimate the MOS from the speech data in a non-intrusive way. We propose two novelties in our work. First, we explore transfer learning by pre-training a model using a larger set of POLQA scores and ﬁnetuning with the smaller (and thus cheaper) human-labeled set. Secondly, we perform a subject-speciﬁc scaling in the MOS scores to adjust for their different subjective scales. Our model yields better accuracy than PESQ, POLQA, and other non-intrusive methods when evaluated on the independent VCTK test set. We also report misleading POLQA scores for reverberant speech.