Miracle-dz/UniFAR-FTUs huggingface dataset:
Arsenic Accumulation in Rice Grain as Influenced by Water Management: Human Health Risk Assessment

Rice is a staple food for humans and a key source of soil arsenic (As) transfer to the human food chain. As a result, it is critical to develop ways for reducing As accumulation in rice. A pot experiment with seven different water management practices was done to examine the impacts of water management on rice (cv. BRRI dhan28) growth, yield, and As accumulation in rice grain. Any health risk due to As accumulation in rice grain was also determined. The soil used in the experiment was artificially contaminated with As and the source of As was sodium arsenate (Na2HAsO4 7H2O). Water management practices affect different plant growth and yield parameters including filled grains per panicle, unfilled grains per panicle, 1000-grain weight, grain yield and straw yield of rice. The number of filled grains per panicle and 1000-grain weight were found to be at their highest in the T7 (alternate wetting and drying) condition, whereas the number of unfilled grains per panicle was at its lowest in the same treatment. The T7 also demonstrated the highest grain yield (21.08 g/pot) and straw yield (22.02 g/pot), whereas the lowest values were noted in T1 (flooding throughout the growth period). The highest As concentration in rice grain (0.52 mg kg−1) was found in T1 and the lowest As concentration in grain (0.27 mg kg−1) was found in T7. Estimation of the human health risk revealed that the non-carcinogenic risks (HQ > 1) and carcinogenic risks (CR > 1.0 × 10−4) were greatly affected by different water regimes. The rice plant grown under alternate wetting and drying condition (T7) showed the lowest health risks compared to other water management practices. Thus, alternate wetting and drying conditions are a good water management strategy for increasing rice output while reducing arsenic buildup in rice grain.
Temporal Context in Speech Emotion Recognition

We investigate the importance of temporal context for speech emotion recognition (SER). Two SER systems trained on traditional and learned features, respectively, are developed to predict categorical labels of emotion. For traditional acoustical features, we study the combination of ﬁlterbank features and prosodic features and the impact on SER when the temporal context of these features is expanded by learnable spectro-temporal receptive ﬁelds (STRFs). Experiments show that the system trained on learnable STRFs outperforms other reported systems evaluated with a similar setup. We also demonstrate that the wav2vec features, pretrained with long temporal context, are superior to traditional features. We then introduce a novel segment-based learning objective to constrain our classiﬁer to extract local emotion features from the large temporal context. Combined with the learning objective and ﬁne-tuning strategy, our top-line system using wav2vec features reaches state-of-the-art performance on the IEMOCAP dataset.
Intellectual Capital And Cost Stickiness: A Modified Value Added Intellectual Coefficient (Mvaic) Approach

This study aims to provide empirical evidence about the relationship between intellectual capital and cost stickiness. Intellectual Capital has been widely studied about its effect on company performance, but still not much has been studied about its effect on cost behavior. Intellectual Capital in this study uses the Modified Value Added Intellectual Capital (MVAIC) approach. The population in this study were all manufacturing companies listed on the Indonesia Stock Exchange (IDX) in 2017 - 2018. The sample in this study was 119 companies which were selected through purposive sampling. The results of this study indicate that the intellectual capital carried out by the company is able to reduce the level of cost stickiness in manufacturing companies in Indonesia. In practice, the IC carried out by the company is able to reduce cost stickiness, so that it can improve the financial performance of the firm.
Training Hybrid Models on Noisy Transliterated Transcripts for Code-Switched Speech Recognition

In this paper, we describe the JHU-GoVivace submission for subtask 2 (code-switching task) of the Multilingual and Code-switching ASR challenges for low resource Indian languages. We built a hybrid HMM-DNN system with several improvements over the provided baseline in terms of lexical, language, and acoustic modeling. For lexical modeling, we investigate us-ing uniﬁed pronunciations and phonesets derived from the base-line lexicon and publicly available Wikipron lexicons in Bengali and Hindi to expand the pronunciation lexicons. We explore several neural network architectures, along with supervised pre-training and multilingual training for acoustic modeling. We also describe how we used large externally crawled web text for language modeling. Since the challenge data contain artefacts such as misalignments, various data cleanup methods are explored, including acoustic-driven pronunciation learning to help discover Indian-accented pronunciations for English words as well as transcribed punctuation. As a result of these efforts, our best systems achieve transliterated WERs of 19.5% and 23.2% on the non-duplicated development sets for Hindi-English and Bengali-English, respectively.
Diabetestherapie im Krankenhaus

ZUSAMMENFASSUNG Eine strukturierte und standardisierte Diabetestherapie im Krankenhaus war noch nie so wichtig wie heute. Die Nebendiagnose Diabetes ist so häufig geworden, dass jede Abteilung sich damit auseinandersetzen muss. Eine Vernachlässigung der Erkrankung hat eine Zunahme von Komplikationen, eine Verlängerung des stationären Aufenthaltes und eine verstärkte Nutzung von teuren Intensivkapazitäten zur Folge. Die Zunahme von Häufigkeit der Erkrankung, Komplexität der vorhandenen Medikamente und häufig erforderlichen Insulintherapie spricht für den Einsatz von ärztlichen und nicht-ärztlichen Fachkräften auf allen Stationen in einem Krankenhaus. Dies kann durch die zentrale Verantwortlichkeit einer Serviceeinheit „Diabetologie“ erreicht werden – so wie es das Zertifikat „Krankenhaus für Diabetiker geeignet“ der Deutschen Diabetes Gesellschaft fordert und fördert.
A Generative Model for Duration-Dependent Score Calibration

In this work we introduce a generative score calibration model for speaker veriﬁcation systems able to explicitly account for utterance-dependent miscalibration sources, with a focus on segment duration. The model is theoretically motivated by an analysis of the effects of distribution mismatch on the scores produced by Probabilistic Linear Discriminant Analysis (PLDA), and extends our previous investigation on the distribution of well-calibrated PLDA log-likelihood ratios. We characterize target and non-target scores by means of Variance-Gamma densities, whose parameters represent effective be-tween and within-class variabilities. Experimental results on SRE 2019 show that the proposed method improves both calibration and veriﬁcation accuracy with respect to duration-agnostic models and to duration-aware discriminative methods.
INFLUENCE OF BASIL OIL AS AN ESSENTIAL OIL ON BUFFALO CALVES PERFORMANCE, DIGESTIBILITY, HAEMOBIOCHEMICAL PROFILE AND RUMEN FERMENTATION INDICATORS

This work was fulfilled to assess the effect of supplementation diets with Basil oil in buffalo calves on growth performance criteria, rumen fermentation properties and certain biochemical indices. A total number of 18 buffalo calves of (4-6) months age and 141.29 kg average body weight were classified randomly into three equal groups (6 animals each): Animals of T1 (control) were fed on basal diet and those of T2 and T3 (treated) were fed as T1 plus 2 and 4 ml basil oil (BO) per head daily, respectively. This experiment was expanded for fifteen weeks. Blood plasma and rumen liquor Samples were obtained from all experimental animals in all groups at the finishing of study for detecting certain blood biochemical parameters and rumen fermentations properties. Results showed that the groups supplemented by basil oil (T2 and T3) recorded significant improvement (P≤0.05) in DM intake, digestibility, growth performance and best feed conversion ratio compared with control group (T1). Also, treated groups (T2 and T3) recorded non observable (P≥0.05) effects in TVFA's, total protozoa count (TPC) and ammonia concentration compared with control group. Blood plasma analysis in supplemented groups (T2 and T3) showed significant improvement (P≤0.05) in protein profile (total protein and albumin), non-significant decrease in urea, creatinine, triglycerides, liver function enzymes levels in comparing with control group. The results collected from this study proposed that buffalo calves fed diets supplemented with basil oil as an essential oil, showed greater total weight gains, daily weight gains, and feed conversion rates with better rumen fermentation parameters.
The Role of Integral Model of Critical Infrastructure Safety in Industry 4.0

: Purpose: This paper aims to create a dedicated tool for managing the level of availability of services delivered by critical infrastructure (CI) facilities, which will affect the Sustainable Development Goals. The paper established a link between sustainability, Industry 4.0, and critical infrastructure. The literature analysis has indicated that the security of Industry 4.0 is discussed almost exclusively in the perspective of cyber security. Design/Methodology/Approach: Verification of the tool was carried out based on simulations and computational experience using data PKN ORLEN Refinery Inc. Findings: As a result of the work carried out, an Integral Model of Critical Infrastructure Safety (IMCIS) was obtained, which allows us to present CI's current characteristics. It was established that the canon of characterization of CI objects consists of a set of resources, a set of functionalities, a set of threats, a set of safeguards, a set of threat dependencies, and a set of dependencies of objects recognized as CI. Practical Implications: A universal application of the IMCIS is to estimate the level of risk before and after implementing safeguards and generating adverse event scenarios. The identified threats are the decision-making areas of the decision problem, whose solution is indicated by a set of safeguards reducing the risk level to an acceptable level. Originality/Value: The solution can be used to identify a set of safeguards that, on the one hand, will reduce the cost of the business operator to a minimum and, on the other hand, achieve the required level of availability of CI functionality. In addition, IMCIS allows analyzing all threats that may affect the infrastructure of Industry 4.0, taking into account many independent decision-making centers.
Emitting Word Timings with HMM-Free End-to-End System in Automatic Speech Recognition

Word timings, which mark the start and end times of each word in ASR results, play an important part in many applications, such as computer assisted language learning. To date, end-to-end (E2E) systems outperform conventional DNN-HMM hybrid systems in ASR accuracy but have challenges to obtain accurate word timings. In this paper, we propose a two-pass method to estimate word timings under an E2E-based LAS modeling framework, which is completely free of using the DNN-HMM ASR system. Speciﬁcally, we ﬁrst employ the LAS system to obtain word-piece transcripts of the input audio, we then compute forced-alignments with a frame-level-based word-piece classiﬁer. In order to make the clas-siﬁer yield accurate word-piece timing results, we propose a novel objective function to learn the classiﬁer, utilizing the spike timings of the connectionist temporal classiﬁcation (CTC) model. On Librispeech data, our E2E-based LAS system achieves 2.8%/7.0% WERs, while its word timing (start/end) accuracy are 99.0%/95.3% and 98.6%/93.7% on test-clean and test-other two test sets respectively. Compared with a DNN-HMM hybrid ASR system (here, TDNN), the LAS sys-tem is better in ASR performance, and the generated word timings are close to what the TDNN ASR system presents.
Experience with valuation methods for the creation of real options enabling diversity of nuclear fuel supply

ABSTRACT Defense in depth is a pillar of nuclear power plant design and it also plays an important factor for the reliability of fuel supply. While most safety systems of a classical light water reactor usually remain unchanged for many years of operation the first and second fission product barrier – the fuel and the cladding – are regularly exchanged by loading fresh fuel assemblies into the reactor core. We review our experience of achieving high reliability in fuel supply by means of real options. The required activities for option creation are explained in detail. Real option valuation is known to be more difficult than financial option valuation and we review the valuation metrics which we found most useful. Due to the incompleteness and illiquidity of the considered option market and due to the barriers of realizing arbitrage, lower and upper bounds are easier to determine than exact option values. Notwithstanding these constraints using concepts based on volatility and stochastic processes in our experience is good practice to avoid naked bets on future power plant availability and avoids the pitfalls of static forecasts.
Optimally Encoding Inductive Biases into the Transformer Improves End-to-End Speech Translation

Transformer-based encoder-decoder architectures have recently shown promising results in end-to-end speech translation. However, the content-based attention mechanism employed by the Transformer was designed for text sequences and can only encode global inductive bias, that alone is not sufﬁcient for learning good representations from speech signals. In this work, we address this by putting architectural constraints on the Trans-former to allow encoding of both local and global inductive biases. This is accomplished by replacing the Transformer encoder with a Conformer encoder that, in contrast to the Transformer encoder, employs convolution in addition to self-attention and feed-forward. As a result, the new model named Conformer-Transformer has an encoder that captures both local feature correlations and long-range dependencies from speech signals. Experiments on seven non-English to English language directions show that the Conformer-Transformer, compared to strong Transformer-based baselines, achieves up to 3 . 54 BLEU score improvements with a pre-trained encoder and up to 10 . 53 BLEU score improvements when trained from scratch.
Differential temperature responses between Plutella xylostella and its specialist endo‐larval parasitoid Diadegma semiclausum—Implications for biological control

Understanding the thermal dynamics of host–parasitoid interactions is crucial to predicting how biological control of pest insects by parasitoids might be affected by geographic location and climate change. We compared performance traits of Plutella xylostella (Lepidoptera: Plutellidae) and its solitary endo‐larval parasitoid Diadegma semiclausum (Hymenoptera: Ichneumonidae), over a wide range of constant rearing temperatures (10–30°C). Parasitoids reared at 30°C experienced reductions in pupation rate, pupal mass, egg load, and adult life span when compared with those reared at lower temperatures. Our analyses of the fate of parasitoids and their hosts and intergenerational population growth at different rearing temperatures show that D. semiclausum and P. xylostella respond differently to temperature, leading to divergent outcomes under different temperature conditions. Some parasitoid larvae could not complete development at 30°C, the temperature at which the host biomass was least and the metabolic demands of the parasitoid could be high, suggesting that parasitoid development might be constrained by lack of host resources at higher temperatures. We discuss the potential mechanisms of parasitoid susceptibility to elevated temperatures, which likely explain the pronounced seasonal dynamics of D. semiclausum in subtropical regions and its failure to establish in lowland tropical regions, where P. xylostella is a serious pest. Similar interactions in other host–parasitoid associations would constrain the efficacy of parasitoids as biological control agents as global temperatures increase.
Fiber Bragg Grating-Based Optical Signal Processing: Review and Survey

This paper reviews the state of the art of fiber Bragg gratings (FBGs) as analog all-optical signal processing units. Besides the intrinsic advantages of FBGs, such as relatively low cost, low losses, polarization insensitivity and full compatibility with fiber-optic systems, they have proven to deliver an exceptional flexibility to perform any complex band-limited spectral response by means of the variation of their physical parameters. These features have made FBGs an ideal platform for the development of all-optical broadband filters and pulse processors. In this review, we resume the main design algorithms of signal processors based on FBGs, and we revisit the most common processing units based on FBGs and the applications that have been presented in the literature.
A new species of Salentinella Ruffo, 1947 from a thermo-mineral cave in southern Spain, with comments on the systematic position of the family Salentinellidae (Amphipoda)

A new species of the stygobiont amphipod genus Salentinella Ruffo, 1947 is described from a thermo-mineral cave of Granada, southern Spain. Detailed observation of the appendages of the new species and of fresh specimens of S. angelieri Delamare-Deboutteville & Ruffo, 1952, and their comparison with the descriptions of other members of the family, have revealed that a simple callynophore is present on the antennule in both sexes of salentinellids. Furthermore, salentinellids have resulted to show a non-senticaudatan (i.e., lack of apical spines on rami) condition of uropods I and II. Both features question the current placement of the family within the senticaudatan parvorder Bogidiellidira. An identification key to all known members of the family Salentinellidae is provided. known from a single specimen, described but left unnamed by Platvoet (1987), but for which Messouli et al. (2018) erected Aposalentinella . This last taxon displays a carpus of both gnathopods that is much shorter than the corresponding propodus, and only six spines on the basal endite of the maxillule. Both features depart from the condition found in other salentinellids, where the carpus of gnathopods is equal or longer than the corresponding propodus, and the basal endite of the maxillule bears nine spines:
Effects of Essential Oils and Aromatic Plants on Alzheimer’s Disease and Dementia

The primary objective of this research was to investigate how beneficial essential oils and aromatic plants are at curing Alzheimer’s disease and dementia. Alzheimer’s Disease (AD) is known to be one of the most incurable prevalent diseases in the elderly. Agitation, cognitive impairments, communication difficulty, irritability, and confusion may advance in AD patients. Even though the behavioral causes contributing to the disease have not yet been discovered, aggregation of tau and amyloid proteins is found in the brain of patients with Alzheimer’s. With numerous experiments conducted on these proteins, scientists have surmised that this accumulation is a causative factor of Alzheimer’s disease. Multiple scientists and experts have carried out several studies regarding the enlargement of amyloid plaques on Alzheimer’s. In addition, the effects of aromatherapy, including divergent results of alternative essential oils, have been analyzed. This paper examines the distinctions between Alzheimer's disease and dementia. The review elaborates on the causes and the symptoms before describing the effects of essential oils and aromatic plants. Subsequently, this provides rudiments regarding the benefits and hazards of applying essential oils and aromatic plants to treat either Alzheimer's disease or dementia. This study focuses on utilizing essential oils and aromatic plants in the medical profession as an alternative treatment for Alzheimer's disease and dementia. Likewise, a couple of case studies are shown in the paper with the analysis of amyloid plaques in mice and the effectiveness of lavender, rosemary, and orange essential oils on participants. Keywords: Alzheimer’s disease Dementia Essential oils Aromatic plants Aromatherapy Amyloid and Tau
A Nonlinear Optimal Control Approach for the Vertical Take-off and Landing Aircraft

The paper proposes a nonlinear optimal control approach for the model of the vertical take-off and landing (VTOL) aircraft. This aerial drone receives as control input a directed thrust, as well as forces acting on its wing tips. The latter forces are not perpendicular to the body axis of the drone but are tilted by a small angle. The dynamic model of the VTOL undergoes approximate linearization with the use of Taylor series expansion around a temporary operating point which is recomputed at each iteration of the control method. For the approximately linearized model, an H-infinity feedback controller is designed. The linearization procedure relies on the computation of the Jacobian matrices of the state-space model of the VTOL aircraft. The proposed control method stands for the solution of the optimal control problem for the nonlinear and multivariable dynamics of the aerial drone, under model uncertainties and external perturbations. For the computation of the controller’s feedback gains, an algebraic Riccati equation is solved at each time-step of the control method. The new nonlinear optimal control approach achieves fast and accurate tracking for all state variables of the VTOL aircraft, under moderate variations of the control inputs. The stability properties of the control scheme are proven through Lyapunov analysis.
Effects of Unidirectional In Situ Stress on Crack Propagation of a Jointed Rock Mass Subjected to Stress Wave

This paper proposes a large-scale experiment combined with multiple cement mortar blocks to simulate stress wave propagation across a jointed rock mass under unidirectional in situ stress. Two identical mortar block models with smooth, dry, and unfilled joints were poured. The stress waves in Model 1 and Model 2 were generated by an electric spark source and a blast-induced source, respectively. The effects of these two excitation sources on stress wave propagation were compared through crack propagation experiments. The experimental results show that the peak value of the transmitted strain wave decreases as the in situ stress increases. The unidirectional in situ stress has a certain inhibitory effect on the stress wave propagation. It also indicates that for Model 1 with the electric spark source, no cracks on the upper surface, but a Livingstone blasting crater at the bottom is generated. For Model 2 with the blast-induced source, cracks on the upper surface and a blasting crater at the bottom are produced. The results verify the similarity between the electric spark source and the explosive source. The two-dimensional finite element program (ANSYS/LS-DYNA) was applied to further simulate the crack propagation of a jointed rock mass under different in situ stresses. The results of numerical simulation verify that the in situ stress has a clear guiding effect on the crack propagation.