Miracle-dz/UniFAR-FTUs huggingface dataset:
Life table- parameters and morphometrics of the corn leaf aphid, Rhopalosiphum maidis (Fitch) (Hemiptera: Aphididae), reared on sorghum host plant

Sorghum is attacked by many insect-pests which are the principal limiting factor for its productivity throughout the country. Corn leaf aphid, Rhopalosiphum maidis is widely distributed and one of important pest on sorghum. The study of biology is important for understanding the form and extent of its population growth. R. maidis on sorghum had a life cycle of 7.79±0.12 days, adult longevity of 12.27±0.27 days, life span of 16.25±0.80 days, fecundity and rate of reproduction 35.97 progenies/female, 9.15 progenies/female/day at 27 ±0.5 0 C. Life table parameters includes net reproduction rate (R 0 ) 45.05, mean generation time (T c ) 9.24, intrinsic rate of natural increase (r m ) 0.44, innate capacity of increase (r c ) 0.41 and corrected mean generation time (T) 8.73 days, respectively. Nymphs developed through four instars and transformed into adults. The length and width of different nymphal stages of R. maidis were: 720.57± 9.95 µm and 303.62 ± 5.59 µm (1 st instar); 978.46 ± 13.51 µm and 412.83 ± 5.53 µm (2 nd instar); 1399.52 ± 24.56 µm and 581.74 ± 12.33 µm (3 rd instar); 1737.5 ± 20.28 µm and 733.98 ± 10.96 µm (4 th instar), respectively. The adult were yellowish green to dark olive green or bluish green and measured 1833.63±15.89 μm in length and 783.26±10.82 μm in width.
Defining Valid Activity Monitor Data: A Multimethod Analysis of Weight-Loss Intervention Participants’ Barriers to Wear and First 100 Days of Physical Activity

Despite the popularity of commercially available wearable activity monitors (WAMs), there is a paucity of consistent methodology for analyzing large amounts of accelerometer data from these devices. This multimethod study aimed to inform appropriate Fitbit wear thresholds for physical activity (PA) outcomes assessment in a sample of 616 low-income, majority Latina patients with obesity enrolled in a behavioral weight-loss intervention. Secondly, this study aimed to understand intervention participants’ barriers to Fitbit use. We applied a heart rate (HR) criterion (≥10 h/day) and a step count (SC) criterion (≥1000 steps/day) to 100 days of continuous activity monitor data. We examined the prevalence of valid wear and PA outcomes between analytic subgroups of participants who met the HR criterion, SC criterion, or both. We undertook qualitative analysis of research staff notes and participant interviews to explore barriers to valid Fitbit data collection. Overall, one in three participants did not meet the SC criterion for valid wear in Weeks 1 and 13; however, we found the SC criterion to be more inclusive of participants who did not use a smartphone than the HR criterion. Older age, higher body mass index (BMI), barriers to smartphone use, device storage issues, and negative emotional responses to WAM-based self-monitoring may predict higher proportions of invalid WAM data in weight-loss intervention research.
l1 Norm Regularization Robust Attitude Smoother Using Inertial and Magnetic Sensors

A smoother algorithm to estimate attitude using inertial and magnetic sensors is proposed, where an attitude estimation problem is formulated as an equality constrained convex optimization problem. Existing standard smoothers are local estimators, whose estimation performance critically depends on the initial estimation. This issue is avoided by formulating an attitude problem as a global optimization problem. An $l_{1}$ regression term is also introduced to make the proposed method robust to sensor outliers (such as temporary magnetic disturbance or external acceleration). The optimization problem is solved through two approximation steps. In the first step, a relaxed solution is computed by relaxing equality constraints to inequality constraints. In the second step, equality constraints are recovered by searching neighborhood of a relaxed solution. Due to the approximation, the proposed algorithm is not guaranteed to provide a globally optimal solution. However, a measure of how close the computed solution is to the globally optimal solution is provided. Through simulation and experiments, the proposed method is shown to be robust to large sensor outliers: the sum of Euler angle rms errors (for 729 different simulations) by the proposed method is 2.974 (rad), while the sum by the standard smoother is 11.52 (rad).
Evaluation of Gas Hydrate Anti-agglomerant Based on Laser Measurement

The feasibility of evaluating the performance of anti-agglomerants from analyzing the variation of morphologies and chord length of particles was examined using an autoclave installed with a particle video microscope and focused beam reflectance measurement probes. The experimental results from methane + water + diesel oil systems show that the agglomeration of hydrate can be judged directly from two laser probes. With the action of an effective anti-agglomerant, the size of droplets/hydrate particles is uniform and tends to that before hydrate formation when most water converts to hydrate or the system stops stirring for 9 h, although the agglomeration occurs when water droplets initially convert into hydrates. The evaluation method was examined under different anti-agglomerant concentrations, water cuts, and subcoolings for water + diesel oil systems. The action mechanism of anti-agglomerants was also proposed.
Play Music: User Motivations and Expectations for Non-Specific Voice Queries

The growing market of voice-enabled devices introduces new types of music search requests that can be more ambiguous than in typed search interfaces as voice assistants can potentially support conversational requests. However, these systems may not be able to fulfill ambiguous requests in a manner that matches the user need. In this work, we study an example of ambiguous requests which we term as non-specific queries (NSQs), such as "play music," where users ask to stream content using a single utterance that does not specify what content they want to hear. To better understand user motivations for making NSQs, we conducted semi-structured qualitative interviews with voice users. We observed four themes that structure user perceptions of the benefits and shortcomings of making NSQs: the tradeoff between control and convenience, varying expectations for personalization, the effects of context on expectations, and learned user behaviors. We conclude with implications for how these themes can inform the interaction design of voice search systems in handling non-specific music requests in voice search systems.
Intermediate Phases during Decomposition of Metal Borohydrides, M(BH4)n (M = Na, Mg, Y)

Ideal materials for hydrogen storage for on-board vehicular applications need to be reversible, store hydrogen with high gravimetric and volumetric density, and operate at near ambient conditions. Although metal borohydrides meet the high-density requirements, the presence of intermediate phases during decomposition adversely affects their reversibility. A fundamental understanding of these phases is, therefore, important before metal borohydrides can be used for practical applications. Recent experiments indicate that the decomposition of NaBH4 yields Na2B12H12 as the intermediate phase, while decomposition of Mg(BH4)2 and Y(BH4)3 yields Mg(B3H8)2 and Y(B3H8)3, respectively. To understand why the intermediate phases are different for Na, Mg, and Y borohydrides, we have carried out systematic first-principles calculations based on density functional theory to investigate the relative stability of M[BH4]n, M[B3H8]n, and M2[B12H12]n (M = Na, Mg, and Y; n is the valence of metal atom). The agreement between .
Longitudinal and Lateral Integration of Conducting Polymer Nanowire Arrays via Block-Copolymer-Templated Electropolymerization

Pyrrole (Py) and thiophene derivatives were electropolymerized on a microphase-separated block copolymer [PEO-b-PMA(Az)] coated ITO electrode in order to form the corresponding conducting polymer nanostructures of perpendicularly oriented and hexagonally arranged cylinders as a template without the removal of one of the domains. Polypyrrole (PPy) nanowires grew through PEO cylindrical domains oriented perpendicular to the electrode to afford an array with an aspect ratio of up to 140 and a density of up to 4.4 × 1012 wires/in.2. Long, straight, π-stacked crystalline structures assigned to PPy main chains were observed in high-resolution TEM images of the individual wires. Additional elaborately crafted electropolymerization was demonstrated on a nanometer scale: (i) stepwise electropolymerization of Py and 3,4-ethylenedioxythiophene (EDOT) afforded segmented PPy–poly(3,4-ethylenedioxythiophene) (PEDOT) and PEDOT–PPy wires with nanoheterojunctions and (ii) one-pot electropolymerization of a mixture of Py a.
The Jazz Harmony Treebank

Grammatical models which represent the hierarchical structure of chord sequences have proven very useful in recent analyses of Jazz harmony. A critical resource for building and evaluating such models is a ground-truth database of syntax trees that encode hierarchical analyses of chord sequences. In this paper, we introduce the Jazz Harmony Treebank (JHT), a dataset of hierarchical analyses of complete Jazz standards. The analyses were created and checked by experts, based on lead sheets from the open iRealPro collection. The JHT is publicly available in JavaScript Object Notation (JSON), a human-understandable and machine-readable format for structured data. We additionally discuss statistical properties of the corpus and present a simple open-source web application for the graphical creation and editing of trees which was developed during the creation of the dataset.
Decision-Making for the Lifetime Performance Index

The purpose of this research is to develop a maximum likelihood estimator (MLE) for lifetime performance index CL for the parameter of mixture Rayleigh-Half Normal distribution (RHN) under progressively type-II right-censored samples under the constraint of knowing the lower specification limit (L). Additionally, we suggest an asymptotic normal distribution for the MLE for CL in order to construct a mechanism for evaluating products' lifespan efficiency. We have specified all the steps to carry out the test. Additionally, not only does hypothesis testing successfully assess the lifetime performance of items, but it also functions as a supplier selection criterion for the consumer. Finally, we have added two real data examples as illustration examples. These two applications are provided to demonstrate how the results can be applied.
Analyse de sentiments dans les textes économiques : un exemple d'application chez ReportLinker

RÉSUMÉ. Cet article présente un retour d’expérience mené dans un cadre industriel sur de l’analyse de sentiments. L’expérience consiste à traiter des données non structurées à partir de dépêches d’actualité en économie aﬁn d’extraire la tonalité des phrases (positives ou négatives). Nous présentons ici la méthode utilisée au sein de notre moteur de recherche, ReportLinker. Il s’agit d’une méthode hybride ; basée sur de la linguistique (lexiques) et de la statistique (modèle de régression logistique). L’article décrit les expérimentations effectuées aboutissant à une meilleure F-mesure et tire les premières conclusions de cette méthode. ABSTRACT. This article presents a feedback from experience carried out in an industrial setting on sentiment analysis. The experiment consists of processing unstructured data from economic news in order to extract the polarity of sentences (positive or negative). We present the method used within our search engine, ReportLinker: a hybrid method; based on linguistics (Lexicons) and statistics (logistic regression model). The article describes the experiments carried out leading to a better F-measure and draws the ﬁrst conclusions from this method.
A New Hybrid Forecasting Model Based on SW-LSTM and Wavelet Packet Decomposition: A Case Study of Oil Futures Prices

The crude oil futures prices forecasting is a significant research topic for the management of the energy futures market. In order to optimize the accuracy of energy futures prices prediction, a new hybrid model is established in this paper which combines wavelet packet decomposition (WPD) based on long short-term memory network (LSTM) with stochastic time effective weight (SW) function method (WPD-SW-LSTM). In the proposed framework, WPD is a signal processing method employed to decompose the original series into subseries with different frequencies and the SW-LSTM model is constructed based on random theory and the principle of LSTM network. To investigate the prediction performance of the new forecasting approach, SVM, BPNN, LSTM, WPD-BPNN, WPD-LSTM, CEEMDAN-LSTM, VMD-LSTM, and ST-GRU are considered as comparison models. Moreover, a new error measurement method (multiorder multiscale complexity invariant distance, MMCID) is improved to evaluate the forecasting results from different models, and the numerical results demonstrate that the high-accuracy forecast of oil futures prices is realized.
Dynamic Dataflow Scheduling and Computation Mapping Techniques for Efficient Depthwise Separable Convolution Acceleration

Depthwise separable convolution (DSC) has become one of the essential structures for lightweight convolutional neural networks. Nevertheless, its hardware architecture has not received much attention. Several previous hardware designs incur either high off-chip memory traffic or large on-chip memory usage, and hence have deficiency in terms of hardware efficiency as well as performance. This paper proposes two efficient dynamic design techniques, i.e. adaptive row-based dataflow scheduling and adaptive computation mapping, to achieve a much better trade-off between hardware efficiency and performance for DSC-based lightweight CNN accelerator. The effectiveness and efficiency of the proposed dynamic design techniques have been extensively evaluated using six DSC-based lightweight CNNs. Compared with the reference architectures, the simulation results show the proposed architectural techniques can at least reduce on-chip buffer size by 50.4% and improve the performance of convolution calculation by $1.18\times $ while maintaining the minimum off-chip memory traffic. MobileNetV2 is implemented on Zynq UltraScale+ ZCU102 SoC FPGA, and the results show the proposed accelerator can achieve 381.7 frames per second (fps), which is $1.43\times $ of the reference design, and it can save about 36.3% on-chip buffer size compared with the reference design, while maintaining the same off-chip memory traffic.
A Deep Clustering Method For Analyzing Uterine Cervix Images Across Imaging Devices

Visual inspection of the cervix with acetic acid (VIA), though error prone, has long been used for screening women and to guide management for cervical cancer. The automated visual evaluation (AVE) technique, in which deep learning is used to predict precancer based on a digital image of the acetowhitened cervix, has demonstrated its promise as a low-cost method to improve on human performance. However, there are several challenges in moving AVE beyond proof-of-concept and deploying it as a practical adjunct tool in visual screening. One of them is making AVE robust across images captured using different devices. We propose a new deep learning based clustering approach to investigate whether the images taken by three different devices (a common smartphone, a custom smartphone-based handheld device for cervical imaging, and a clinical colposcope equipped with SLR digital camera-based imaging capability) can be well distinguished from each other with respect to the visual appearance/content within their cervix regions. We argue that disparity in visual appearance of a cervix across devices could be a significant confounding factor in training and generalizing AVE performance. Our method consists of four components: cervix region detection, feature extraction, feature encoding, and clustering. Multiple experiments are conducted to demonstrate the effectiveness of each component and compare alternative methods in each component. Our proposed method achieves high clustering accuracy (97%) and significantly outperforms several representative deep clustering methods on our dataset. The high clustering performance indicates the images taken from these three devices are different with respect to visual appearance. Our results and analysis establish a need for developing a method that minimizes such variance among the images acquired from different devices. It also recognizes the need for large number of training images from different sources for robust device-independent AVE performance worldwide.
An Ohio State Scenic River Shows Elevated Antibiotic Resistance Genes, Including Acinetobacter Tetracycline and Macrolide Resistance, Downstream of Wastewater Treatment Plant Effluent

The entry of antibiotic resistance genes (ARGs) into aquatic systems has been documented for large municipal wastewater treatment plants, but there is less study of the impact of smaller plants that are situated on small rural rivers. We sampled water metagenomes for ARG and taxa composition from the Kokosing River, a small rural river in Knox County, Ohio, which has been designated an Ohio State Scenic River for retention of natural character. Samples were obtained 1.0 km upstream, 120 m downstream, and 6.4 km downstream from the effluent release of the Mount Vernon wastewater treatment plant (WWTP). ARGS were identified in metagenomes using ShortBRED markers from the CARD database screened against UniPROT. Through all seasons, the metagenome just downstream of the WWTP effluent showed a substantial elevation of at least 15 different ARGs, including 6 ARGs commonly associated with Acinetobacter baumannii such as msrE, mphE (macrolide resistance) and tet(39) (tetracycline resistance). The ARGs most prevalent near the effluent pipe persisted 6.4 km downriver. Using MetaPhlAn2 clade-specific marker genes, the taxa distribution near the effluent showed elevation of reads annotated as Acinetobacter species as well as gut-associated taxa, Bacteroides and Firmicutes. The ARG levels and taxa prevalence showed little dependence on seasonal chlorination of the effluent. Nitrogen and phosphorus were elevated near the effluent pipe but had no consistent correlation with ARG levels. We show that in a rural river microbiome, year-round wastewater effluent substantially elevates ARGs including those associated with multidrug-resistant A. baumanii. IMPORTANCE Antibiotic resistance is a growing problem worldwide, with frequent transmission between pathogens and environmental organisms. Rural rivers can support high levels of recreational use by people unaware of inputs from treated wastewater, while WWTPs can generate a small but significant portion of flow volume into a river surrounded by forest and agriculture. There is little information on the rural impacts of WWTP effluent on the delivery and transport of antibiotic resistance genes. In our study, the river water proximal to wastewater effluent shows evidence for the influx of multidrug-resistant Acinetobacter baumanii, an opportunistic pathogen of concern for hospitals but also widespread in natural environments. Our work highlights the importance of wastewater effluent in management of environmental antibiotic resistance, even in high quality, rural river systems.
Prediction of Heart Disease Using a Combination of Machine Learning and Deep Learning

The correct prediction of heart disease can prevent life threats, and incorrect prediction can prove to be fatal at the same time. In this paper different machine learning algorithms and deep learning are applied to compare the results and analysis of the UCI Machine Learning Heart Disease dataset. The dataset consists of 14 main attributes used for performing the analysis. Various promising results are achieved and are validated using accuracy and confusion matrix. The dataset consists of some irrelevant features which are handled using Isolation Forest, and data are also normalized for getting better results. And how this study can be combined with some multimedia technology like mobile devices is also discussed. Using deep learning approach, 94.2% accuracy was obtained.
Continuous Wheat in Semiarid Regions: Long-term Effects on Stock and Quality of Soil Organic Carbon

Abstract Continuous wheat (Triticum aestivum L.) cropping in semiarid regions results in variable dry matter production. As a consequence, the balance of soil organic carbon (SOC) may vary across time. The aim of this research was to assess the dynamics and long-term changes of physically and chemically extracted SOC fractions. Soil samples (0- to 5-, 5- to 10-, and 10- to 20-cm depths) from continuous wheat with (f) and without (nf) fertilizer (N + P) under conventional tillage ((CT) for 25 years) and no-tillage ((NT) for 6 years) were taken during the experiment. Mineral-associated ((MOC) 0–0.053 mm), fine particulate ((POCf) 0.053–0.100 mm), and coarse particulate ((POCc) 0.1–2.0 mm) SOC and humic substances were obtained. The SOC variability depended on water availability during fallow periods (SOC decomposition) or crop cycles (dry matter production). The mean wheat yields were 1.33 (nf) and 2.09 (f) Mg grain ha−1, with an estimated carbon input of 1.64 (nf) and 2.20 (f) Mg C ha−1 year−1. Losses from the initial level were higher in labile fractions, POCc (−75%) and POCf (−53%), than in MOC (−15%). Humic acids present slight differences in their structure and quantity as a result of long-term cropping. Conversion from CT to NT resulted in contrasting results. For an equivalent soil mass, fertilizer application increased SOC by 4.31 Mg ha−1 (under CT) and 7.29 Mg ha−1 (under NT). The SOC turned out to be higher under NT with fertilizer use and lower without application. No-tillage does not increase SOC content by itself; it must be combined with other agricultural practices such as fertilization and/or crop rotation.
Balanced and Unbalanced Duplexers Using Common Oval Dielectric Resonators

In this paper, dual-mode oval dielectric resonator (DR) is proposed as common resonator to realize all four kinds of balanced and unbalanced duplexers. The conventional topology is replaced with the novel one of sharing input and output dual-mode resonators at the same time for miniaturization. By adjusting the aspect ratio and height of the oval DR, the two modes are separated properly to form two channels of duplexers. After locating probes delicately according to the orthogonality of dual-mode fields, the channel transmission and isolation are ensured simultaneously under sharing output DR. Moreover, both dual-mode unbalanced and balanced operations are studied to extend the topology to all four kinds of duplexers. For verification, balanced-to-unbalanced (B-U) and balanced-to-balanced (B-B) duplexers are both fabricated and tested. Low insertion losses better than 0.59 dB are achieved in both two designs. High isolations lower than −36 dB and −50 dB and common-mode rejections lower than −44 dB and −52 dB are observed in the B-U and B-B duplexers, respectively. The exhibited high performance with reduced resonators demonstrates the potentials of the proposed duplexers in miniaturized FDD communication systems for connecting balanced/unbalanced transceivers with balanced/unbalanced antennas.