Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of automatic visual attention in schizophrenia, bipolar disorder, and major depression: Evidence from P1 event‐related component

The ability to discern commonalities and differences in the neurobiology of functional psychoses represents a key element to unmasking shared vulnerability across different psychiatric conditions. The present study sought to compare the automatic visual attention mechanisms in three psychiatric disorders considered to distribute along the continuum of psychosis severity: schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD). To this end, the visual P1 event‐related potential component, a cortical correlate of automatic visual attention, was measured during an ecological task based on visual word pair presentation.
Factors Influencing the Intention to Continue using B2B e-Commerce in Manufacturing SMEs

Business-to-Business (B2B) electronic commerce plays a tremendous role in nurturing the growth of Small and Medium Enterprises (SMEs) in developed and developing countries. However, the growth of B2B e-commerce in developing nations remains at the early adoption stage. The purpose of this paper is to examine the factors that influence B2B e-commerce adoption in SMEs in a developing country. The current study employs the questionnaire survey technique to gather information from 245 manufacturing SMEs in Jordan. It uses Structural Equation Modeling (SEM) to investigate the different factors that affect the intention to adopt or continue using B2B e-commerce. The study reveals that compatibility and outsourcing IT support have significant effects on the intention to continue using B2B e-commerce in Jordanian manufacturing SMEs. The implications of the findings are discussed.
Molecular investigation of non-volant endemic mammals through mitochondrial cytochrome b gene from Andaman and Nicobar archipelago

Abstract The shrews, Crocidura andamanensis, Crocidura nicobarica (order Eulipotyphla), and treeshrew, Tupaia nicobarica, (order Scandentia) are highly threatened mammals; endemic to Andaman and Nicobar archipelago. The aimed study provides the first baseline mitochondrial cytochrome b (mtCytb) genetic information of Crocidura and Tupaia species from Andaman and Nicobar Island. The mtCytb data were well discriminated against to all three studied species from their congeners with sufficient genetic distance. Crocidura andamanensis showed less genetic distance (13%) with Crocidura grayi, while high (21.3%) with Crocidura phuquocensis. Besides, the C. nicobarica showed less distance (5.5%) with Crocidura vosmaeri and Crocidura beccarii, while high (19%) with C. phuquocensis. Both C. andamanensis and C. nicobarica also depicted a 15.6% genetic distance with each other. Further, the treeshrew species T. nicobarica is apparently discriminated by other congeners with a sufficient genetic distance ranging from 8.8 to 25.5%. The maximum-likelihood (ML) topology distinctly discriminated against all the shrews and treeshrews species with significant bootstrap supports. The aimed study fortifies the efficacy of mtCytb gene to segregate the above discussed non-volant mammal species. We recommended the widespread noninvasive sampling and genotyping to elucidate the population structure, which assists to formulate the precise conservation measures to protect these unique mammals.
Biological and biogeochemical methods for estimating bioirrigation: a case study in the Oosterschelde estuary

Abstract. Bioirrigation, the exchange of solutes between overlying water and sediment by benthic organisms, plays an important role in sediment biogeochemistry. Bioirrigation either is quantified based on tracer data or a community (bio)irrigation potential (IPc) can be derived based on biological traits. Both these techniques were applied in a seasonal study of bioirrigation in subtidal and intertidal habitats in a temperate estuary. The combination of a tracer time series with a high temporal resolution and a mechanistic model allowed for us to simultaneously estimate the pumping rate and the sediment attenuation, a parameter that determines irrigation depth. We show that, although the total pumping rate is similar in both intertidal and subtidal areas, there is deeper bioirrigation in intertidal areas. This is explained by higher densities of bioirrigators such as Corophium sp. , Heteromastus filiformis and Arenicola marina in the intertidal, as opposed to the subtidal, areas. The IPc correlated more strongly with the attenuation coefficient than the pumping rate, which highlights that the IPc index reflects more the bioirrigation depth than the rate.
Ultrawideband Low-Profile and Miniaturized Spoof Plasmonic Vivaldi Antenna for Base Station

Stable radiation pattern, high gain, and miniaturization are necessary for the ultra-wideband antennas in the 2G/3G/4G/5G base station applications. Here, an ultrawideband and miniaturized spoof plasmonic antipodal Vivaldi antenna (AVA) is proposed, which is composed of the AVA and the loaded periodic grooves. The designed operating frequency band is from 1.8 GHz to 6 GHz, and the average gain is 7.24 dBi. Furthermore, the measured results show that the radiation patterns of the plasmonic AVA are stable. The measured results are in good agreement with the simulation results.
Isolation and identification of some bacteria causing subclinical mastitis in cows

Isolation and identification of different type of bacteria from milk samples of 20 clinically healthy cow from different area in Mosul city between the period from May 2007 to May 2008 was carried out. The quality of the milk was screened using white side test. Identification of the isolate was carried out depend on the morphology of colony and biochemical test. The results indicated that total percentage of the infectivity of milk was (80%). The coagulase negative Staphyloccoci (CNS) was dominant. The more frequent from them was Staphylococcus sciuri which was (21.8%) followed by Staphylococcus aureus (18.7%), Streptococcus spp. (15.6%) then G -ve Coccobacill, Arcanobacterium pyogenes (9.3%) and Micoccocus (3.1%). Staphylococcus sciuri and CNS were more sensitive to Chloramphenicol and Ciprofloxacin but resistance to Ampicillin and Penicillin G. Available online at http://www.vetmedmosul. org/ijvs
Development and disassembly of single and multiple acid-cleavable block copolymer nanoassemblies for drug delivery

Drug delivery via block copolymer nanoassemblies has been widely viewed as an efficient way to augment therapeutic efficiency of anticancer drugs for cancer therapy. Acid-degradable block copolymer-based nanoassemblies are promising intracellular candidates for tumor-targeting drug delivery as they exhibit enhanced release of encapsulated drugs through their dissociation (or disintegration) upon cleavage of acid-labile linkages in response to a tumor's acidic environment (pH = 4.2–6.7). Furthermore, degradation of the self-assemblies via acid-catalyzed hydrolysis can be tuned with a choice of various available acid-labile linkages. This review summarizes recent advances in the synthesis and disassembly of acid-cleavable block copolymers for controlled drug delivery. Strategies to integrate acid-labile covalent linkages in block copolymers at different locations, as in micelle cores and core/corona interfaces are particularly focused upon. Additionally, elegant strategies that allow for the synthesis of dual acid/reduction, acid/light, acid/enzyme-degradable block copolymer systems with cleavable linkages in single or dual locations are discussed.
Unprecedented disruptions of lives and work: Health, distress and life satisfaction of working adults in China one month into the COVID-19 outbreak

We assess the health and wellbeing of normal adults living and working after one month of confinement to contain the COVID-19 outbreak in China. On Feb 20 and 21, 2020, we surveyed 369 adults in 64 cities in China that varied in their rates of confirmed coronavirus cases on their health conditions, distress and life satisfaction. 27% of the participants worked at the office, 38% resorted to working from home, and 25% stopped working due to the outbreak. Those who stopped working reported worse mental and physical health conditions as well as distress. The severity of COVID-19 in a location predicts life satisfaction, and this relationship is contingent upon the existing chronic health issues and hours of exercise of the individuals. Our evidence supports the need to pay attention to the health of people who were not affected by the virus epidemiologically, especially for people who stopped working during the outbreak. Our results highlight that physically active people might be more susceptible to wellbeing issues during the lockdown. Policymakers who are considering introducing restrictive measures to contain COVID-19 may benefit from understanding such health and wellbeing implications.
Artificial Neural Network and Kalman Filter for Estimation and Control in Standalone Induction Generator Wind Energy DC Microgrid

This paper presents an improved estimation strategy for the rotor flux, the rotor speed and the frequency required in the control scheme of a standalone wind energy conversion system based on self-excited three-phase squirrel-cage induction generator with battery storage. At the generator side control, the rotor flux is estimated using an adaptive Kalman filter, and the rotor speed is estimated based on an artificial neural network. This estimation technique enhances the robustness against parametric variations and uncertainties due to the adaptation mechanisms. A vector control scheme is used at the load side converter for controlling the load voltage with respect to amplitude and frequency. The frequency is estimated by a Kalman filter method. The estimation schemes require only voltage and current measurements. A power management system is developed to operate the battery storage in the DC-microgrid based on the wind generation. The control strategy operates under variable wind speed and variable load. The control, estimation and power management schemes are built in the MATLAB/Simulink and RT-LAB platforms and experimentally validated using the OPAL-RT real-time digital controller and a DC-microgrid experimental setup.
Spatiotemporal Distribution and Risk Assessment of Heat Waves Based on Apparent Temperature in the One Belt and One Road Region

Heat waves seriously affect the productivity and daily life of human beings. Therefore, they bring great risks and uncertainties for the further development of countries in the One Belt and One Road (OBOR) region. In this study, we used daily meteorological monitoring data to calculate the daily apparent temperature and annual heat wave dataset for 1989–2018 in the OBOR region. Then, we studied their spatiotemporal distribution patterns. Additionally, multi-source data were used to assess heat wave risk in the OBOR region. The main results are as follows: (1) The daily apparent temperature dataset and annual heat wave dataset for 1989–2018 in the OBOR region at 0.1° × 0.1° gridded resolution were calculated. China, South Asia and Southeast Asia are suffering the most serious heat waves in the OBOR region, with an average of more than six heat waves, lasting for more than 60 days and the extreme apparent temperature has reached over 40 °C. Additionally, the frequency, duration and intensity of heat waves have been confirmed to increase continuously. (2) The heat wave risk in the OBOR region was assessed. Results show that the high heat wave risk areas are distributed in eastern China, northern South Asia and some cities. The main conclusion is that the heat wave risk in most areas along the OBOR route is relatively high. In the process of deepening the development of countries in the OBOR region, heat wave risk should be fully considered.
Data-driven refactorings for Haskell

Agile software development allows for software to evolve slowly over time. Decisions made during the early stages of a program's lifecycle often come with a cost in the form of technical debt. Technical debt is the concept that reworking a program that is implemented in a naive or "easy" way, is often more difficult than changing the behaviour of a more robust solution. Refactoring is one of the primary ways to reduce technical debt. Refactoring is the process of changing the internal structure of a program without changing its external behaviour. The goal of performing refactorings is to increase code quality, maintainability, and extensibility of the source program. Performing refactorings manually is time consuming and error-prone. This makes automated refactoring tools very useful. Haskell is a strongly typed, pure functional programming language. Haskell's rich type system allows for complex and powerful data models and abstractions. These abstractions and data models are an important part of Haskell programs. This thesis argues that these parts of a program accrue technical debt, and that refactoring is an important technique to reduce this type of technical debt. Refactorings exist that tackle issues with a program's data model, however these refactorings are specific to the object-oriented programming paradigm. This thesis reports on work done to design and automate refactorings that help Haskell programmers develop and evolve these abstractions. This work also discussed the current design and implementation of HaRe (the Haskell Refactorer). HaRe now supports the Glasgow Haskell Compiler's implementation of the Haskell 2010 standard and its extensions, and uses some of GHC's internal packages in its implementation.
Grouped attribute strength-based image retrieval

Abstract. Visual attributes, as a bridge between humans and machines, have played an important role in various applications. We focus on attribute-based image retrieval. Unlike early works that either initiate the image search via binary attributes or refine the search results via relative attributes, we propose to realize image retrieval using grouped attribute strength, which are learned from both binary attributes and relative attributes. First, early methods are employed to predict the binary attributes and sort the relative attributes in descending order in different situations. Second, we group the sorted images corresponding to each attribute and combine the learned binary and relative attributes to learn the grouped attribute strength of the images, which result in a new attribute feature vector for each image. Finally, we apply the learned grouped attribute strength to different retrieval models to realize our image retrieval tasks. We demonstrate the approach on LFW-10 and Shoes datasets and show its clear advantages over traditional binary attribute-based retrieval methods.
Does Trade Liberalisation Policy Enhance Performance of Non-Oil Export Trade in Nigeria?

Decades after the trade liberalisation policy shift, poor performance problem of non-oil export in Nigeria (a net-oil exporting economy) persists. Against this backdrop, and given the lack of analytical depth among Nigerian-specific studies, this study empirically provided answer to the question of whether trade liberalisation policy enhances non-oil export trade in Nigeria. The study adopted an Autoregressive Distributed Lag model approach to the analysis of the impact of trade liberalisation policy on non-oil export trade. Evidence provided support for trade liberalisation policy as the growth driver for non-oil export, a sector that exports more but earns little in terms of revenue. As a result, the study recommends a well thought-out public–private partnership arrangement for the efficiency of the private sector (a major player in non-oil export trade), to optimally harness the benefits of liberalisation in Nigeria’s non-oil trade sub-sector. JEL Codes: F14, F17, F41, F62
Dual comb spectroscopy using silicon electro-optical modulators

Optical frequency combs (OFCs) have played an important role over the past years for optical frequency metrology and synthesis, for astronomy, telecommunications, and spectroscopy. Among the different methods that have been studied for OFC generation, electro-optic frequency combs (EOFCs) using electro-optical modulators show a large flexibility in comb repetition rate, making it a solution of choice for absorption spectroscopy where a fine sampling in the frequency domain is usually required. Silicon photonics is a promising platform for EOFC generation, thanks to its high volume production and strong light confinement allowing to achieve small footprint photonic integrated circuits (PICs). Additionally, silicon PICs benefit from a direct compatibility with complementary metal-oxide semiconductor (CMOS) fabrication process. Carrier depletion-based modulators have already proved to be efficient and to achieve high bandwidth operation, which makes them suitable for EOFC generation. In this work we will show the first dual comb spectroscopy experiment using silicon optical modulators. As a proof of concept for spectroscopy applications, beating of two silicon EOFCs with slightly different repetition rates is observed in the RF domain using a multi-heterodyne detection technique. Each EOFC is generated from a silicon push-pull Mach-Zehnder modulator and shows typically 12 equally separated lines. The comb repetition rate is swept from 500 MHz to 12.5 GHz, thanks to the inherent flexibility of EOFCs, while their relative offset is kept steady (4 MHz). This technique is used to recover the transfer function of an optical band-pass filter without any tunable laser.
Stand development moderates effects of ungulate exclusion on foliar traits in the forests of New Zealand

1. Ungulate herbivores may greatly alter the functional composition of plant communities through their selection of leaves with high nutrient concentrations and low structural or chemical defences. These impacts may have broader implications for ecosystem functions via changing rates of litter decomposition and the relative abundance of foliar traits. However, it is unlikely that ungulate impacts will be consistent across different vegetation types and different environmental conditions.
Mobile Introns: Pathways and Proteins

While the role of group I and group II intron-encoded proteins in homing has been well defined, the function of these proteins in intron dissemination to new sites remains the subject of intense study. These mobile introns, their intron-encoded proteins, and the mechanisms by which mobility occurs are the subject of this chapter. Although transition metals are not required for colicin DNase activity, it is likely that they play a stabilizing role related to the membrane translocation that must occur for colicin’s biological function. These data lend credence to the idea that the HNH domain, like the GIY-YIG domain, is an endonu clease cassette that can become associated with other protein domains to form multifunctional proteins. The open reading frames (ORFs) specifying group II intron-encoded proteins, when present, are located in the loop region of the structural domain IV, with most of the coding sequence outside the intron catalytic core. Of the three activities of the group II intron-encoded proteins, the maturase domain is present in all known cases. Endonuclease activity of an intron-encoded protein was first shown for the yeast mtDNA introns aI1 and aI2. Group I and group II introns are self-splicing elements with wide genomic distribution, reflecting their dispersal through active mobility mechanisms. These two types of introns represent different ways in which selfish elements exploit functions that promote their invasiveness. Basic research into the structure and function of intron-encoded proteins and of the dynamics of mobility pathways is yielding a refined view of their modus operandi.
A Data-Driven Approach With Uncertainty Quantification for Predicting Future Capacities and Remaining Useful Life of Lithium-ion Battery

Predicting future capacities and remaining useful life (RUL) with uncertainty quantification is a key but challenging issue in the applications of battery health diagnosis and management. This article applies advanced machine-learning techniques to achieve effective future capacities and RUL prediction for lithium-ion (Li-ion) batteries with reliable uncertainty management. To be specific, after using the empirical mode decomposition (EMD) method, the original battery capacity data is decomposed into some intrinsic mode functions (IMFs) and a residual. Then, the long short-term memory (LSTM) submodel is applied to estimate the residual while the Gaussian process regression (GPR) submodel is utilized to fit the IMFs with the uncertainty level. Consequently, both the long-term dependence of capacity and uncertainty quantification caused by the capacity regenerations can be captured directly and simultaneously. Experimental aging data from different batteries are deployed to evaluate the performance of proposed LSTM+GPR model in comparison with the solo GPR, solo LSTM, GPR+EMD, and LSTM+EMD models. Illustrative results demonstrate the combined LSTM+GPR model outperforms other counterparts and is capable of achieving accurate results for both 1-step and multistep ahead capacity predictions. Even predicting the RUL at the early battery cycle stage, the proposed data-driven approach still presents good adaptability and reliable uncertainty quantification for battery health diagnosis.
60 GHz Compact Larger Beam Scanning Range PCB Leaky-Wave Antenna Using HMSIW for Millimeter-Wave Applications

A half-mode substrate integrated waveguide (HMSIW), based on printed circuit board (PCB) technology, is employed to construct a novel $V$ -band leaky-wave antenna incorporating composite right-/left-handed (CRLH) media. Including modified half-sinusoidally varied interdigital capacitive slots on the radiating edge of the HMSIW enables the feature of effective CRLH media to produce adequate radiation coverage and bandwidth with improved sidelobe level (SLL) and higher gain. Unit cell characteristics and space harmonic analysis were thoroughly investigated through dispersion and Bloch impedance analysis. By appropriately tuning the physical parameters of the design, the balanced condition was obtained at a broadside frequency of 60 GHz. The highly directed radiated fan beam covered a scanning range of 120° with beam steering from −72° to 48° of the visible space. The proposed antenna operated over 55–65 GHz with a maximum realized gain of 14.5 dBi, maximum beamwidth of 9.15°, better than 15 dB SLL and 20 dB cross-polar radiation. All simulated responses showed reasonably good accordance with experimental data thereby validating the novel design of the proposed leaky-wave structure for millimeter-wave wireless applications.