Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors Influencing Safety Efficacy: Examining Past Experience, Mind-Set, and Emotion Management

Safety efficacy, or the perceived capability of preventing or deterring a personal safety threat, has emerged as a potentially important construct in personal safety outcomes. However, there has been limited research on factors that may facilitate or inhibit safety efficacy. The overall goal of this study was to examine indices of past history, mind-set, and emotion regulation associated with safety efficacy as informed by the self-efficacy literature. This study used a national sample of 821 women who completed a survey on personal safety concerns and responses. There were four main findings from this study: (a) although victimization experiences in this study were high, there were no differences in past or recent victimization experiences by safety efficacy group; (b) responding passively and feeling uncomfortable and nervous in interpersonal conflict situations were significantly associated with lower safety efficacy; (c) those with lower safety efficacy felt less confident in protecting themselves, were less likely to feel they could affect the outcome of external events, were less likely to seek information about their personal safety, and were more likely to feel personal characteristics increased their risk of victimization; and (d) discomfort when thinking about personal safety as well as emotion regulation problems were negatively associated with safety efficacy, yet have received limited research attention with regard to their role in personal safety outcomes. More research is needed to build on the success of various interventions that have shown evidence of increased safety efficacy and decreased revictimization as well as to reach women who may actively avoid prevention programs because they are not comfortable thinking about their safety.
Genome Wide Transcriptome Analysis Reveals Complex Regulatory Mechanisms Underlying Phosphate Homeostasis in Soybean Nodules

Phosphorus (P) deficiency is a major limitation for legume crop production. Although overall adaptations of plant roots to P deficiency have been extensively studied, only fragmentary information is available in regard to root nodule responses to P deficiency. In this study, genome wide transcriptome analysis was conducted using RNA-seq analysis in soybean nodules grown under P-sufficient (500 μM KH2PO4) and P-deficient (25 μM KH2PO4) conditions to investigate molecular mechanisms underlying soybean (Glycine max) nodule adaptation to phosphate (Pi) starvation. Phosphorus deficiency significantly decreased soybean nodule growth and nitrogenase activity. Nodule Pi concentrations declined by 49% in response to P deficiency, but this was well below the 87% and 88% decreases observed in shoots and roots, respectively. Nodule transcript profiling revealed that a total of 2055 genes exhibited differential expression patterns between Pi sufficient and deficient conditions. A set of (differentially expressed genes) DEGs appeared to be involved in maintaining Pi homeostasis in soybean nodules, including eight Pi transporters (PTs), eight genes coding proteins containing the SYG1/PHO81/XPR1 domain (SPXs), and 16 purple acid phosphatases (PAPs). The results suggest that a complex transcriptional regulatory network participates in soybean nodule adaption to Pi starvation, most notable a Pi signaling pathway, are involved in maintaining Pi homeostasis in nodules.
Impact of Integrated Circuit Packaging on Synaptic Dynamics of Memristive Devices

The memristor can be used as non volatile memory (NVM) and for emulating neuron behavior. It has the ability to switch between low resistance $R_{on}$ and high resistance values $R_{off}$, and exhibit the synaptic dynamic behaviour such as potentiation and depression. This paper presents a study on potentiation and depression of memristors in Quad Flat Pack. A comparison is drawn between the memristors with and without the impact of parasitics of packaging, using measured data and equivalent circuit models. The parameters in memristor and packaging models for the SPICE simulations were determined using measured data to reflect the memristor parasitics in Quad Flat Packs.
Impact of Private Domestic Investment on Economic Growth in Nigeria

One of the major economic problems in the developing nation like Nigeria is low domestic investment finance. The vicious cycle of low domestic investment finance as a result of low savings lead to low capital formation and this has become a cankerworm which has eaten deep into the fabric of the Nigerian economy. Despite government policies such as export promotion and bank recapitalization policy at boosting investment, all these efforts have not yielded appreciable results in order for domestic investment to increase economic growth. It is against this back drop that the study examined the impact of private domestic investment on economic growth in Nigeria. The objectives of this study were to; examined how private domestic investment and private sector credits from financial institution affect economic growth. The study covered the period of 1980-2016 with the analytical techniques relying on Kwiatkowski–Phillips–Schmidt–Shin (KPSS) stationarity and Johansen system cointegration tests as well as Error Correction Mechanism (ECM). The result of the KPSS stationarity test showed that the variables are first difference stationary. More so, the Johansen test results for cointegration indicated that the variables are cointegrated and as such have the capability of moving together in the long run. The parsimonious Error Correction Short Research Article Bidemi et al.; AJEBA, 9(2): 1-9, 2018; Article no.AJEBA. 45698 2 Mechanism showed that private domestic investment is significantly related to economic growth. The result indicated that holding other variables, 10 percent increase in the current value of private domestic investment, on the average, stimulates economic growth by 2.08 percent. Similarly, the value of financial sector credit to private sector is positively related to economic growth. On the average, a percent increase in financial sector credit to private sector boost growth in Nigeria by 2.27 percent. Owing to the findings, it is recommended among others that Private domestic investment should be promoted across key sectors of the economy, especially agriculture and manufacturing activities in order to stimulate rapid and sustained growth in Nigeria.
The Association Between the Processing of Binaural Temporal-Fine-Structure Information and Audiometric Threshold and Age: A Meta-Analysis

The ability to process binaural temporal fine structure (TFS) information, which influences the perception of speech in spatially distributed soundscapes, declines with increasing hearing loss and age. Because of the relatively small sample sizes used in previous studies, and the population-unrepresentative distribution of hearing loss and ages within study samples, it has been difficult to determine the relative and combined contributions of hearing loss and age. The aim of this study was to survey published and unpublished studies that assessed binaural TFS sensitivity using the TFS-low frequency (LF) test. Results from 19 studies were collated, yielding sample sizes of 147 to 648, depending on the test frequency. At least for the test frequency of 500 Hz, there were at least 67 listeners in each of four adult age groups and the distribution of audiometric thresholds at the test frequency within each group was similar to that for the population as a whole. Binaural TFS sensitivity declined with increasing age across the adult lifespan and with increasing hearing loss in old adulthood. For all test frequencies, both audiometric threshold and age were significantly negatively correlated with TFS-LF sensitivity (r ranging from −0.19 to −0.64) but the correlation was always significantly higher for age than for audiometric threshold. Regression analyses showed that the standardized regression coefficient was greater for age than for audiometric threshold, and that there was a significant interaction; the effect of increasing age among older listeners was greater when the hearing loss was ≥30 dB than when it was < 30 dB.
The effects of supplemental threonine on performance, carcass characteristics, immune response and gut health of broilers in subtropics during pre‐starter and starter period

Three hundred thirty-day-old unsexed commercial broiler chicks (Vencobb-400) with initial average body weight of 44.04 ± 0.42 g were allocated into five experimental groups, in a completely randomized design (CRD) with 21-day experiment. Groups were formed according to dose of supplemental L-threonine in various rations i.e., 100% NRC specification, 100% threonine of Vencobb-400 strain specification, 110% threonine of Vencobb-400 strain specification, 120% of threonine of Vencobb-400 strain specification and 130% threonine of Vencobb-400 strain specification. Average daily feed intake (ADFI), average daily body weight gain (ADG), cumulative feed conversion ratio (CFCR), carcass characteristics, immune response, intestinal morphometry and biochemical profile were studied. The ADFI and ADG increased linearly and quadratically as dietary threonine levels were increased. However, the CFCR did not differ (p ˃ 0.05) among the groups. Though the carcass weight and drumstick yield did not differ (p ˃ 0.05) among the groups, the relative breast yield increased linearly (p = 0.007). The relative dressing yield and relative thigh weight increased linearly (p = 0.05 and p = 0.03, respectively). The relative weight of immune organs like bursa and thymus increased linearly. The mean total serum immunoglobulin, ND-ELISA titre and the mean lymphocyte proliferation response index increased linearly, whereas mean phagocytic activity index of neutrophil increased linearly (p < 0.001) and quadratically (p = 0.001). The mean villus height (VH), crypt depth (CD), villus surface area and mean goblet cell number/villus increased linearly and quadratically, whereas the villus width (VW) and goblet cell density increased quadratically. The serum glucose increased linearly (p = 0.001), whereas serum total protein concentration and serum globulin level increased both linearly and quadratically. The albumin: globulin ratio tended to decrease linearly. There was a significant decrease (p < 0.05) in serum cholesterol and VLDL cholesterol level. However, a linear increment (p = 0.04) in the blood serum HDL cholesterol level with a linear reduction (p = 0.01) in the blood serum LDL cholesterol was noticed.
Efficient decoding of interleaved subspace and Gabidulin codes beyond their unique decoding radius using Gröbner bases

An interpolation-based decoding scheme for L-interleaved subspace codes is presented. The scheme can be used as a (not necessarily polynomial-time) list decoder as well as a polynomial-time probabilistic unique decoder. Both interpretations allow to decode interleaved subspace codes beyond half the minimum subspace distance. Both schemes can decode γ insertions and δ deletions up to γ + Lδ ≤ L(nt − k), where nt is the dimension of the transmitted subspace and k is the number of data symbols from the field Fqm. Further, a complementary decoding approach is presented which corrects γ insertions and δ deletions up to Lγ +δ ≤ L(nt −k). Both schemes use properties of minimal Gr¨obner bases for the interpolation module that allow predicting the worst-case list size right after the interpolation step. An efficient procedure for constructing the required minimal Gr¨obner basis using the general K¨otter interpolation is presented. A computationally- and memory-efficient root-finding algorithm for the probabilistic unique decoder is proposed. The overall complexity of the decoding algorithm is at most O(L2n2 r) operations in F qm where nr is the dimension of the received subspace and L is the interleaving order. The analysis as well as the efficient algorithms can also be applied for accelerating the decoding of interleaved Gabidulin codes.
Controlling the Wetting Properties of Superhydrophobic Titanium Surface Fabricated by UV Nanosecond-Pulsed Laser and Heat Treatment

In this study, the effects of nanosecond-pulsed laser and pattern design were researched on the wettability of titanium material. Nanosecond-pulsed laser and heat treatment are used to fabricate superhydrophobic titanium surfaces. The effects of laser power (1–3 W) and step size (50–300 µm) on a microscale patterned titanium surface (line pattern and grid pattern) were investigated to explain the relation between microstructure and superhydrophobicity. The surface morphologies and wettability of the surfaces were analyzed by three-dimensional confocal microscopy and a contact angle meter. The results show that the laser power and pattern design affected the apparent contact angle (CA) and sliding angle (SA). The maximum step size, which could show superhydrophobicity with apparent CA > 150° and SA < 10°, was increased when the laser power increased from 1 to 3 W. Grid pattern showed isotropic wetting behavior, but line pattern showed both isotropic and anisotropic wetting behavior according to step size and laser power. Furthermore, when choosing the proper laser power and step size, the wetting properties of superhydrophobic surface such as lotus effect (apparent CA > 150° and SA < 10°) and petal effect (apparent CA > 150° and no SA) and isotropic/anisotropic behavior can be controlled for applications of water droplet control.
Acute Lymphoblastic Leukemia Detection and Classification of Its Subtypes Using Pretrained Deep Convolutional Neural Networks

Leukemia is a fatal disease of white blood cells which affects the blood and bone marrow in human body. We deployed deep convolutional neural network for automated detection of acute lymphoblastic leukemia and classification of its subtypes into 4 classes, that is, L1, L2, L3, and Normal which were mostly neglected in previous literature. In contrary to the training from scratch, we deployed pretrained AlexNet which was fine-tuned on our data set. Last layers of the pretrained network were replaced with new layers which can classify the input images into 4 classes. To reduce overtraining, data augmentation technique was used. We also compared the data sets with different color models to check the performance over different color images. For acute lymphoblastic leukemia detection, we achieved a sensitivity of 100%, specificity of 98.11%, and accuracy of 99.50%; and for acute lymphoblastic leukemia subtype classification the sensitivity was 96.74%, specificity was 99.03%, and accuracy was 96.06%. Unlike the standard methods, our proposed method was able to achieve high accuracy without any need of microscopic image segmentation.
Hybrid performance evaluation of sustainable service and manufacturing supply chain management: An integrated approach of fuzzy dematel and fuzzy inference system

The aim of this paper is to propose a comprehensive framework for simultaneously measuring the performance of sustainable service and manufacturing supply chain management. Application of the proposed approach also results in reduced uncertainty of the performance measurement process caused by qualitative criteria evaluation. The proposed approach consists of two main steps. First, the fuzzy decision‐making trial and evaluation laboratory (DEMATEL) method has been used to determine important criteria by avoiding low influences; and then a Mamdani fuzzy inference system model has been adopted and applied for performance evaluation of sustainable supply chain management (SSCM). This model is employed in order to cope with the vagueness that exists in the SSCM performance investigation due to the vagueness intrinsic in the evaluation of criteria. In the proposed model, human reasoning has been modelled with fuzzy inference rules and has been set in the system, which is an advantage compared with those models in which fuzzy set theory and multicriteria decision‐making models are integrated. The proposed approach has been implemented in the pipe and fitting industry in order to highlight its application in real life. Sensitivity analysis has been carried out to determine the influence of service and manufacturing criteria on SSCM performance. The findings reveal that sustainable manufacturing criteria compared with sustainable service criteria have more effect on the performance of SSCM.
Brain asymmetry in directing attention during dichotic listening test: An fNIRS study

ABSTRACT In a classical dichotic listening paradigm, besides auditory brain asymmetry, cognitive functions such as attention and conflict resolution play a major role. The aim of this study is to reveal the possible haemodynamic mechanisms of higher attentional performance in prefrontal cortex during dichotic listening test. Twenty-six healthy participants underwent a dichotic listening task in three sessions; non-forced attention, attention focused to right ear, and attention focused to left ear. In each session, haemodynamic activity of prefrontal brain area was recorded using functional near-infrared spectroscopy (fNIRS). Effects of focused attention and performance level of the task on oxy-, deoxy-, and total haemoglobin levels were investigated. Oxy- and total haemoglobin levels in right prefrontal regions during forced-right and forced-left sessions were significantly higher than levels of the non-forced session. This might be an indicator of inhibition and orienting attentional functions of right inferior frontal gyrus. High performers had significantly higher deoxyhaemoglobin levels in the forced-left session compared to the non-forced session, while low performers’ deoxyhaemoglobin levels did not differ among these sessions. Observing this difference only in the forced-left session but not in the forced-right session might suggest conflict resolution in top-down and bottom-up processes during the forced-left session for right-handed participants.
Higher titer hyaluronic acid production in recombinant Lactococcus lactis

Abstract Hyaluronic acid (HA) is a natural biopolymer and has long been attracting the attention of biotechnology industry due to its various biological functions. HA production with natural producer Streptococcus equi subsp. zooepidemicus has not been preferred because it has many drawbacks due to its pathogenicity. Therefore, in the present study, Streptococcal hyaluronan synthase gene (hasA) was introduced and expressed in Lactococcus lactis, through the auto inducible NICE system and the effect of nisin amount on the production of HA was examined. Newly constructed plasmid was transformed into L. lactis CES15, produced 6.09 g/l HA in static flask culture after three hours of induction period with initial 7.5 ng/ml nisin concentration within total six hours of incubation. The highest HA titer value ever was reported for recombinant HA-producing L. lactis by examining the effect of initial nisin concentration. We have shown that initial nisin concentration, which used to initiate the auto-inducing mechanism of NICE system and consequently hyaluronan synthase expression, has a direct and significant effect on the produced HA amount. Recently constructed recombinant L. lactis CES15 strain provide significant advantages for industrial HA production than those in literature in terms of production time, energy demand, carbon usage, and safety status.
Implicit Mind Perception Alters Vigilance Performance Because of Cognitive Conflict Processing

Knowing the internal states of others is essential to predicting behavior in social interactions and requires that the general characteristic of “having a mind” is granted to our interaction partners. Mind perception is a highly automatic process and can potentially cause a cognitive conflict when interacting with agents whose mind status is ambiguous, such as artificial agents. We investigate whether mind perception negatively impacts performance on tasks involving artificial agents because of cognitive conflict processing caused by a potentially increased difficulty to categorize them as human versus nonhuman. Experiment 1 shows that an ambiguous humanoid stimulus negatively impacts performance on a vigilance task that is known to be sensitive to the drainage of cognitive resources. This negative effect on performance vanishes when participants are preexposed to the stimulus before the vigilance task (Experiment 2 and 3). The effect of preexposure on performance recovery is independent of whether participants explicitly resolve the cognitive conflict by answering mind-related questions (Experiment 2) or implicitly by judging the stimuli on a set of physical features (Experiment 3). Together, the findings suggest that mind perception is so automatic that it cannot be suppressed even if it has negative effects on cognitive performance.
A Decoding Scheme for Incomplete Motor Imagery EEG With Deep Belief Network

High accuracy decoding of electroencephalogram (EEG) signal is still a major challenge that can hardly be solved in the design of an effective motor imagery-based brain-computer interface (BCI), especially when the signal contains various extreme artifacts and outliers arose from data loss. The conventional process to avoid such cases is to directly reject the entire severely contaminated EEG segments, which leads to a drawback that the BCI has no decoding results during that certain period. In this study, a novel decoding scheme based on the combination of Lomb-Scargle periodogram (LSP) and deep belief network (DBN) was proposed to recognize the incomplete motor imagery EEG. Particularly, instead of discarding the entire segment, two forms of data removal were adopted to eliminate the EEG portions with extreme artifacts and data loss. The LSP was utilized to steadily extract the power spectral density (PSD) features from the incomplete EEG constructed by the remaining portions. A DBN structure based on the restricted Boltzmann machine (RBM) was exploited and optimized to perform the classification task. Various comparative experiments were conducted and evaluated on simulated signal and real incomplete motor imagery EEG, including the comparison of three PSD extraction methods (fast Fourier transform, Welch and LSP) and two classifiers (DBN and support vector machine, SVM). The results demonstrate that the LSP can estimate relative robust PSD features and the proposed scheme can significantly improve the decoding performance for the incomplete motor imagery EEG. This scheme can provide an alternative decoding solution for the motor imagery EEG contaminated by extreme artifacts and data loss. It can be beneficial to promote the stability, smoothness and maintain consecutive outputs without interruption for a BCI system that is suitable for the online and long-term application.
Aspect Term Extraction Based on MFE-CRF

This paper is focused on aspect term extraction in aspect-based sentiment analysis (ABSA), which is one of the hot spots in natural language processing (NLP). This paper proposes MFE-CRF that introduces Multi-Feature Embedding (MFE) clustering based on the Conditional Random Field (CRF) model to improve the effect of aspect term extraction in ABSA. First, Multi-Feature Embedding (MFE) is proposed to improve the text representation and capture more semantic information from text. Then the authors use kmeans++ algorithm to obtain MFE and word clustering to enrich the position features of CRF. Finally, the clustering classes of MFE and word embedding are set as the additional position features to train the model of CRF for aspect term extraction. The experiments on SemEval datasets validate the effectiveness of this model. The results of different models indicate that MFE-CRF can greatly improve the Recall rate of CRF model. Additionally, the Precision rate also is increased obviously when the semantics of text is complex.