bluuebunny/crossref_metadata_2025 huggingface dataset:
Anauralia: The Silent Mind and Its Association With Aphantasia
Authors: Hinwar Rish P. , Lambert Anthony J.
Published: October 2021

Auditory and visual imagery were studied in a sample of 128 participants, including 34 self-reported aphantasics. Auditory imagery (Bucknell Auditory Imagery Scale-Vividness, BAIS-V) and visual imagery (Vividness of Visual Imagery Questionnaire-Modified, VVIQ-M) were strongly associated, Spearman's rho = 0.83: Most self-reported aphantasics also reported weak or entirely absent auditory imagery; and participants lacking auditory imagery tended to be aphantasic. Similarly, vivid visual imagery tended to co-occur with vivid auditory imagery. Nevertheless, the aphantasic group included one individual with typical auditory imagery; and the group lacking auditory imagery (N = 29) included one individual with typical visual imagery. Hence, weak visual and auditory imagery can dissociate, albeit with low apparent incidence. Auditory representations and auditory imagery are thought to play a key role in a wide range of psychological domains, including working memory and memory rehearsal, prospective cognition, thinking, reading, planning, problem-solving, self-regulation, and music. Therefore, self-reports describing an absence of auditory imagery raise a host of important questions concerning the role of phenomenal auditory imagery in these domains. Because there is currently no English word denoting an absence of auditory imagery, we propose a new term, anauralia, for referring to this, and offer suggestions for further research.
Anankastia or Psychoticism? Which One Is Better Suited for the Fifth Trait in the Pathological Big Five: Insight From the Circumplex of Personality Metatraits Perspective
Authors: Strus Włodzimierz , Łakuta Patryk , Cieciuch Jan
Published: October 2021

Both the ICD-11 and the DSM-5 (Section III) classification systems introduced dimensional models of personality disorders, with five broad domains calledthe Pathological Big Five. Nevertheless, despite large congruence between the two models, there are also substantial differences between them, with the most evident being the conceptualization of the fifth dimension: Anankastia in the ICD-11 vs. Psychoticism in the DSM-5. The current paper seeks an answer to the question of which domain is structurally better justified as the fifth trait in the dimensional model of personality disorders. For this purpose, we provided both a conceptual and empirical comparison of the ICD-11 and the DSM-5 models, adopting the Circumplex of Personality Metatraits—a comprehensive model of personality structure built on the basis of the higher-order factors of the Big Five—as a reference framework. Two studies were conducted: the first on a sample of 242 adults (52.9% female;Mage= 30.63,SDage= 11.82 years), and the second on a sample of 355 adults (50.1% female;Mage= 29.97,SDage= 12.26 years) from the non-clinical population. The Personality Inventory for ICD-11 (PiCD), the Personality Inventory for DSM-5 (PID-5), and the Circumplex of Personality Metatraits Questionnaire–Short Form (CPM-Q-SF) were administered in both studies, together with the PID-5BF+M algorithm for measuring a common (ICD-11 + DSM-5) six-domain model. Obtained empirical findings generally support our conceptual considerations that the ICD-11 model more comprehensively covered the area of personality pathology than the DSM-5 model, with Anankastia revealed as a more specific domain of personality disorders as well as more cohesively located within the overall personality structure, in comparison to Psychoticism. Moreover, the results corroborated the bipolar relations of Anankastia vs. Disinhibition domains. These results also correspond with the pattern of relationships found in reference to the Big Five domains of normal personality, which were also included in the current research. All our findings were discussed in the context of suggestions for the content and conceptualization of pathological personality traits that flow from the CPM as a comprehensive model of personality structure including both pathological and normal poles of personality dimensions.
Impact of the COVID-19 Lockdown in Malaysia: An Examination of the Psychological Well-Being of Parent-Child Dyads and Child Behavior in Families With Children on the Autism Spectrum
Authors: Fong Hui Xian , Cornish Kim , Kirk Hannah , Ilias Kartini , Shaikh Mohd Farooq , Golden Karen Jennifer
Published: October 2021

Background: The COVID-19 pandemic lockdowns have adversely impacted children on the autism spectrum and their families, especially in Malaysia where this population is often marginalized. The current quantitative research aimed to investigate the impact of the Malaysian COVID-19 lockdown on the behavior and psychological distress of children formally diagnosed with an autism spectrum condition (ASC) as well as the psychological distress and well-being of their parents, in comparison with a typically developing (TD) control group.

Methods: The children's ages ranged between 5 and 17 years. The sample included 72 ASC parent-child dyads and 62 TD parent-child dyads. The primary caregiver completed an online survey including the following: demographic and diagnostic information; ASC symptoms; children's inattention, hyperactivity/impulsivity, perceived stress, depression, and anxiety; parents' perceived stress, depression, anxiety, and well-being based on their experience pre- and mid-lockdown (March 18th to June 9th 2020) in Malaysia.

Results: Among the ASC group, no significant pre- and mid-lockdown change was found in ASC symptoms (p > 0.05). There were no significant gender differences (boys/girls) in all the child scales. The 2 [diagnosis (ASC, TD)] × 2 [lockdown (pre-lockdown, mid-lockdown)] mixed-model ANOVAs revealed main effects of lockdown on children's attention, hyperactivity/impulsivity, anxiety, and parents' perceived stress, depression, and psychological well-being (p < 0.005). There was a main effect of diagnosis in all child and parent variables, except parents' perceived stress (p >0.005). However, there was no significant interaction effect between diagnosis and lockdown (p >0.005). All child behavior (inattention and hyperactivity/impulsivity) and child psychological distress (anxiety, depression, and perceived stress) were significantly correlated in both the ASC and TD groups (p < 0.005). On the other hand, only some of the parent variables were significantly correlated with child variables (p < 0.0045) in the ASC group while none of the parent variables were significantly correlated with the child variables (p > 0.005) in the TD group.

Conclusion: The results provide preliminary evidence indicating negative effects of the Malaysian lockdown on both children on the autism spectrum and TD children, as well as their parents. These quantitative results will be triangulated with the qualitative interview data to provide a holistic understanding of the impact of the pandemic, informing translational policy and practice recommendations.
Insights Into Adolescents' Substance Use in a Low–Middle-Income Country During the COVID-19 Pandemic
Authors: Sen Lee Thung , Siste Kristiana , Hanafi Enjeline , Murtani Belinda Julivia , Christian Hans , Limawan Albert Prabowo , Adrian  , Siswidiani Levina Putri
Published: October 2021

Introduction: The COVID-19 pandemic and its lockdown have been a significant life event for many individuals, particularly adolescents. The immense psychological pressure could drive risky behavior, e.g., substance use, while lockdown might lead to decreased use. This study aimed to observe the change in substance use among adolescents in Indonesia and the moderating variables to consumption during the COVID-19 lockdown period.

Methods: This study utilized an online survey from April 28, 2020 to June 30, 2020. The hyperlink was disseminated to school administrators and parenting groups through social media and direct messages. A total of 2,932 adolescents (17.4 ± 2.24 and 78.7% females) submitted valid responses. The survey was comprised of a sociodemographic section, substance use details, and psychometric sections, including the Alcohol Use Disorders Identification Test (AUDIT), Cigarette Dependence Scale 12 (CDS-12), Pittsburgh Sleep Quality Index (PSQI), and Strength and Difficulties Questionnaire (SDQ).

Results: Overall, adolescent alcohol use during the pandemic was 5.1%, cigarette smoking was 3.1%, and drug consumption was 0.4%. Over half (53.4%) of alcohol drinkers reported increased drinking, and 33.1% had harmful or dependence-like drinking behavior; in contrast, 44.4% of adolescent smokers disclosed reduced cigarette consumption. Around 37.8% of the drug users indicated increased use. During the pandemic, adolescent alcohol use was associated with higher education [adjusted odds ratio (AOR) = 2.67, 95% confidence interval (CI) 1.02–4.86, p = 0.04], higher AUDIT scores (AOR = 1.33, 95% CI 1.25–1.42, p < 0.001), and very low prosocial behavior (AOR = 2.46, 95% CI 1.52–3.88, p < 0.001). Cigarette smoking was correlated with male sex (AOR = 9.56, 95% CI 5.64–16.62, p < 0.001), age (AOR = 1.40, 95% CI 1.14–1.75, p < 0.001), and higher CDS score (AOR = 1.17, 95% CI 1.13–1.20, p < 0.001).

Conclusions: Rates of adolescent substance use were significant, with sizeable proportions reporting higher usage. This appeared to occur predominantly in specific demographics and those with a lower protective psychosocial attribute, i.e., prosocial behavior, during the lockdown. These findings should urge the strengthening of adolescent addiction care during and after the pandemic.
All-Cause Mortality Risk Associated With Solid Fuel Use Among Chinese Elderly People: A National Retrospective Longitudinal Study
Authors: Shen Shisi , Luo Min , Meng Xuchen , Deng Ying , Cheng Shuwen
Published: October 2021

Background: The adverse health effects of air pollutants are widely reported, and the elderly are susceptible to toxic environments. This study aimed to evaluate the association between use of solid fuels for cooking and mortality among the elderly.

Methods: A total of 5,732 and 3,869 participants from the Chinese Longitudinal Healthy Longevity Survey were enrolled in two (2014 and 2018) and three surveys (2011, 2014, and 2018) of survey. Cooking fuel was divided into clean and solid fuel. Cox proportional hazards models were used to estimate the mortality hazard ratio (HR). Subgroup analyses were performed to assess the potential interaction effect.

Results: Among the participants in the 2011–2018 survey, 53% reported using solid fuel. Such group was associated with a 9% increase in mortality risk relative to clean fuel users (HR = 1.09, 95% CI = 1.01–1.18). Among participants in the 2014–2018 survey, 339 reported a switch from solid to clean fuels and they were not at increased mortality risk relative to the 488 people that reported a stable use of clean fuels (HR = 1.14, 95% CI = 0.99–1.31) although the estimated HR was similar to the one for stable solid fuel users (HR = 1.19, 95%CI = 1.04–1.36 n = 509). Interaction and stratified analyses showed that solid fuel use had an impact on mortality in participants who were non-current smokers, had low dietary diversity scores, and were living in areas with high PM2.5 concentrations (>50 μg/m3) and city population below 8 million (P for interaction < 0.05). The association was robust in the three sensitivity analyses.

Conclusion: The finding showed a clear association between solid fuel use and mortality among older Chinese, and an even stronger association between risk of mortality and solid fuel use among individuals exposed to high levels of PM2.5.
Edge Intelligence in Private Mobile Networks for Next-Generation Railway Systems
Authors: Asad Syed Muhammad , Tahir Ahsen , Rais Rao Naveed Bin , Ansari Shuja , Abubakar Attai Ibrahim , Hussain Sajjad , Abbasi Qammer H. , Imran Muhammad Ali
Published: October 2021

The integration of Private Mobile Networks (PMN) with edge intelligence is expected to play an instrumental role in realizing the next generation of industry applications. This combination collectively termed Intelligent Private Networks (IPN) deployed within the scope of specific industries such as transport systems can unlock several use cases and critical applications that in turn can address rising business demands. This article presents a conceptual IPN that hosts intelligence at the network edge employing emerging technologies that satisfy a number of Next-Generation Railway System (NGRS) applications. NGRS use cases along with their applications and respective beyond 5G (B5G) enabling technologies have been discussed along with possible future research and development directions that will allow these promising technologies to be used and implemented widely.
Shapes Determine Elections
Authors: Ward Erika L.
Published: October 2021

When we elect representatives to the U.S. House of Representatives (or to state legislative bodies, or even the school board), we do so by dividing people into districts, and having each district elect one representative. The districts we draw as shapes on maps can affect the outcome of the elections. As a result, the process of creating or changing districts and the shapes we draw to create them are important. After every census, each state must construct a new district map. When they do that unfairly, it can give an unfair advantage to one of the political parties. This is called gerrymandering. By looking at the shapes of districts and examining their compactness, we can start to detect fair and unfair district maps.
Dynamics of Salivary Adenosine Deaminase, Haptoglobin, and Cortisol in Lipopolysaccharide-Challenged Growing Pigs
Authors: Sali Virpi , Veit Christina , Valros Anna , Junnikkala Sami , Heinonen Mari , Nordgreen Janicke
Published: October 2021

Infectious and inflammatory conditions are common especially in growing pigs. Lipopolysaccharide (LPS) is an important antigenic structure of Gram-negative bacteria and can be used to induce inflammation experimentally. As pigs are usually group-housed in commercial conditions, it is difficult to detect sick individuals, particularly at an early stage of illness. Acute phase proteins such as haptoglobin (Hp) are known indicators of an activated innate immune system whereas adenosine deaminase (ADA) is a relatively novel inflammatory biomarker in pigs. Both parameters can be measured in saliva and could be used as indicators of inflammation. Compared with blood sampling, saliva sampling is a less stressful procedure that is rapid, non-invasive and easy to perform both at group and at individual level. In this blinded randomized clinical trial, 32 female pigs at their post-weaning phase were allocated to one of four treatments comprising two injections of the following substance combinations: saline-saline (SS), ketoprofen-saline (KS), saline-LPS (SL), and ketoprofen-LPS (KL). First, ketoprofen or saline was administered intramuscularly on average 1 h before either LPS or saline was given through an ear vein catheter. In all groups, saliva was collected prior to injections (baseline) and at 4, 24, 48, and 72 h post-injection for determination of ADA, Hp, and cortisol concentrations. A multivariate model was applied to describe the dynamics of each biomarker. Pairwise relationships between ADA, Hp, and cortisol responses from baseline to 4 h post-injection within the SL group were studied with Spearman correlations. A significant increase in the SL group was seen in all biomarkers 4 h post-injection compared to baseline and other time points (pairwise comparisons, p < 0.01 for all) and ketoprofen alleviated the LPS effect. We found a significant positive correlation between ADA and Hp within the SL group (r = 0.86, p < 0.05). The primary and novel findings of the present study are the response of ADA to LPS, its time course and alleviation by ketoprofen. Our results support the evidence that ADA and Hp can be used as inflammatory biomarkers in pigs. We suggest further studies to be conducted in commercial settings with larger sample sizes.
Case Report: Synucleinopathy Associated With Phalaris Neurotoxicity in Sheep
Authors: Tayebi Mourad , Pinczowski Pedro , Habiba Umma , Khan Rizwan , David Monique A. , Summers Brian A.
Published: October 2021

Chronic intoxication with tryptamine-alkaloid-rich Phalaris species (spp.) pasture plants is known colloquially as Phalaris staggers syndrome, a widely occurring neurological disorder of sheep, cattle, horses, and kangaroos. Of comparative interest, structurally analogous tryptamine-alkaloids cause experimental parkinsonism in primates. This study aimed to investigate the neuropathological changes associated with spontaneous cases of Phalaris staggers in sheep with respect to those encountered in human synucleinopathy. In sheep affected with Phalaris staggers, histological, immunohistochemical, and immunofluorescence analysis revealed significant accumulation of neuromelanin and aggregated α-synuclein in the perikaryon of neurons in the cerebral cortex, thalamus, brainstem, and spinal cord. Neuronal intracytoplasmic Lewy bodies inclusions were not observed in these cases of ovine Phalaris staggers. These important findings established a clear link between synucleinopathy and the neurologic form of Phalaris plant poisoning in sheep, demonstrated in six of six affected sheep. Synucleinopathy is a feature of a number of progressive and fatal neurodegenerative disorders of man and may be a common endpoint of such disorders, which in a variety of ways perturb neuronal function. However, whether primary to the degenerative process or a consequence of it awaits clarification in an appropriate model system.
Prevalence of Mastitis Pathogens and Antimicrobial Susceptibility of Isolates From Cattle and Buffaloes in Northwest of Pakistan
Authors: Ali Tariq , Kamran  , Raziq Abdur , Wazir Inamullah , Ullah Rafi , Shah Pervaiz , Ali Muhammad Ijaz , Han Bo , Liu Gang
Published: October 2021

Mastitis is the most prevalent disease of dairy animals, imparting huge economic losses to the dairy industry. There is always a dire need to monitor the prevalence of mastitis, its bacteriology, and evaluation of antimicrobial susceptibilities for mastitis control and prevention. Therefore, the objectives of this study were to investigate: (i) the prevalence of mastitis in cattle and buffaloes; (ii) identification of bacteria associated with mastitis; (iii) antimicrobial susceptibility of bacterial isolates. Milk samples (n = 1,566) from cattle (n = 1,096) and buffaloes (n = 470) were processed for detection of mastitis using the California mastitis test in the year 2018–19. A total of 633 mastitic milk samples were further processed for bacteriology and antimicrobial susceptibility testing by the disc diffusion method. Overall, the prevalence of clinical and subclinical mastitis was 17 and 57% in both species. Clinical mastitis was higher in cattle (20%) compared to buffaloes (11%), whereas subclinical was higher in buffaloes (66%) than cattle (53%). Besides, month-wise prevalence was higher in hot and humid months in both species. Staphylococci spp. (34%) were the most predominant bacterial isolates from mastitic milk, followed by Escherichia coli (19.4%), Streptococci spp. (9%), and Klebsiella spp. (8%). Most of the bacteria were susceptible to gentamicin (92%) and enrofloxacin (88%), when a panel of 16 different antimicrobials was tested. Nevertheless, most of the isolates were resistant to sulphamethoxazole (99%), lincomycin (98%), oxytetracycline (89%), ampicillin (86%), and doxycycline (85%). This study concludes a high prevalence of mastitis caused by Staphylococcal spp. in cattle and buffaloes belonging to the northwest of Pakistan, and gentamicin and enrofloxacin might be appropriate antimicrobial agents in the treatment of bovine mastitis.
Gut Microbial Alterations in Diarrheal Baer's Pochards (Aythya baeri)
Authors: Xi Li , Qin Xinxi , Song Yumin , Han Jincheng , Li Zhiqiang , Zhang Jinliang
Published: October 2021

The structure and composition of gut microbiota correlate with the occurrence and development of host health and disease. Diarrhea can cause alterations in gut microbiota in animals, and the changes in the gut microbial structure and composition may affect the development of diarrhea. However, there is a scarcity of information on the effects of diarrhea on gut fungal composition and structure, particularly in Baer's pochard (Aythya baeri). The current study was performed for high-throughput sequencing of the fungal-specific internal transcribed spacer 1 (ITS-1) to detect the differences of gut mycobiota in healthy and diarrheal Baer's pochard. Results showed that the gut mycobiota not only decreased significantly in diversity but also in structure and composition. Statistical analysis between two groups revealed a significant decrease in the abundance of phylum Rozellomycota, Zoopagomycota, Mortierellomycota, and Kickxellomycota in diarrheal Baer's pochard. At the genus levels, fungal relative abundance changed significantly in 95 genera, with 56 fungal genera, such as Wickerhamomyces, Alternaria, Penicillium, Cystofilobasidium, and Filobasidium, increasing significantly in the gut of the diarrheal Baer's pochard. In conclusion, the current study revealed the discrepancy in the gut fungal diversity and community composition between the healthy and diarrheal Baer's pochard, laying the basis for elucidating the relationship between diarrhea and the gut mycobiota in Baer's pochard.
Development and Characterization of a Novel Porous-Media Borosilicate Glass Ion Sources for Electrospray Thruster
Authors: Yang Yuntian , Guo Dawei , Li Xiaokang , Deng Leimin , Che Bixuan , Cheng Mousen
Published: October 2021

The porous-media-based electrospray thruster is a cutting-edge micropropulsion technology that can revolutionize the capabilities of microsatellites. This paper reports the design, fabrication, and characterization of a novel porous-media borosilicate glass electrospray thruster. The porous glass used here is integrally formed by the phase separation method, which make it display outstanding pore uniformity and processability. The picosecond ultraviolet laser processing technique is applied to machine 361 emitters out of glass. Performance characteristic experiments are conducted with the thruster passively fed with ionic EMI-BF4 liquid. The results reveal that the per-emitter can emit up to 200.46 nA of ion current at 2 kV. The novel porous glass and the corresponding machine method present an opportunity to attain more-controllable emitter shapes, which has a positive impact on thruster lifetime and performance improvement.
Air Traffic Prediction as a Video Prediction Problem Using Convolutional LSTM and Autoencoder
Authors: Kim Hyewook , Lee Keumjin
Published: October 2021

Accurate prediction of future air traffic situations is an essential task in many applications in air traffic management. This paper presents a new framework for predicting air traffic situations as a sequence of images from a deep learning perspective. An autoencoder with convolutional long short-term memory (ConvLSTM) is used, and a mixed loss function technique is proposed to generate better air traffic images than those obtained by using conventional L1 or L2 loss function. The feasibility of the proposed approach is demonstrated with real air traffic data.
A Comparison of IPCC Guidelines and Allocation Methods to Estimate the Environmental Impact of Barley Production in the Basque Country through Life Cycle Assessment (LCA)
Authors: del Hierro Óscar , Gallejones Patricia , Besga Gerardo , Artetxe Ainara , Garbisu Carlos
Published: October 2021

This study aimed to estimate the environmental impact of barley production in the Basque Country, Northern Spain, using cradle-to-gate life cycle assessment (LCA) methodology, as well as to assess how methodological choices (i.e., the use of IPCC 2019 Guidelines versus allocation methods) can influence such estimation. The production of mineral fertiliser and the direct emissions of nitrous oxide (N2O) resulting from the application of nitrogen (N) fertiliser were identified as the two main contributors (40% and 30% of all greenhouse gas emissions, respectively) to the environmental impact of barley production. Pertaining to GHG emissions themselves, the use of calcium ammonium nitrate fertiliser was found to be the main contributor. Therefore, the optimization of N fertiliser application was established as a key process to reduce the environmental impact of barley production. The fertiliser-related release of N and phosphorous (P) to the environment was the main contributor to particulate matter formation, terrestrial acidification, and terrestrial and marine eutrophication. The incorporation of environmental data on NH3, NOx, NO3−, and PO43− to the LCA led to a more accurate estimation of barley production impact. A sensitivity analysis showed that the use of economic allocation, compared to mass allocation, increased the estimation of climate change-related impact by 80%. In turn, the application of the IPCC 2019 Refinement Guidelines increased this estimation by a factor of 1.12 and 0.86 in wet regions and decreased in dry regions, respectively. Our results emphasise the importance of the choice of methodology, adapted to the specific case under study, when estimating the environmental impact of food production systems.
Response of Bromus valdivianus (Pasture Brome) Growth and Physiology to Defoliation Frequency Based on Leaf Stage Development
Authors: Ordóñez Iván P. , López Ignacio F. , Kemp Peter D. , Donaghy Daniel J. , Zhang Yongmei , Herrmann Pauline
Published: October 2021

The increase in drought events due to climate change have enhanced the relevance of species with greater tolerance or avoidance traits to water restriction periods, such as Bromus valdivianus Phil. (B. valdivianus). In southern Chile, B. valdivianus and Lolium perenne L. (L. perenne) coexist; however, the pasture defoliation criterion is based on the physiological growth and development of L. perenne. It is hypothesised that B. valdivianus needs a lower defoliation frequency than L. perenne to enhance its regrowth and energy reserves. Defoliation frequencies tested were based on B. valdivianus leaf stage 2 (LS-2), leaf stage 3 (LS-3), leaf stage 4 (LS-4) and leaf stage 5 (LS-5). The leaf stage development of Lolium perenne was monitored and contrasted with that of B. valdivianus. The study was conducted in a glasshouse and used a randomised complete block design. For Bromus valdivianus, the lamina length, photosynthetic rate, stomatal conductance, tiller number per plant, leaf area, leaf weights, root growth rate, water-soluble carbohydrates (WSCs) and starch were evaluated. Bromus valdivianus maintained six live leaves with three leaves growing simultaneously. When an individual tiller started developing its seventh leaf, senescence began for the second leaf (the first relevant leaf for photosynthesis). Plant herbage mass, the root growth rate and tiller growth were maximised at LS-4 onwards. The highest leaf elongation rate, evaluated through the slope of the lamina elongation curve of a fully expanded leaf, was verified at LS-4. The water-soluble carbohydrates (WSCs) increased at LS-5; however, no statistical differences were found in LS-4. The LS-3 and LS-2 treatments showed a detrimental effect on WSCs and regrowth. The leaf photosynthetic rate and stomatal conductance diminished while the leaf age increased. In conclusion, B. valdivianus is a ‘six-leaf’ species with leaf senescence beginning at LS-4.25. Defoliation at LS-4 and LS-5 was optimum for plant regrowth, maximising the aboveground plant parameters and total WSC accumulation. The LS-4 for B. valdivianus was equivalent to LS-3.5 for L. perenne. No differences related to tiller population in B. valdivianus were found in the different defoliation frequencies.
Deep Learning Models for Automatic Makeup Detection
Authors: Alzahrani Theiab , Al-Bander Baidaa , Al-Nuaimy Waleed
Published: October 2021

Makeup can disguise facial features, which results in degradation in the performance of many facial-related analysis systems, including face recognition, facial landmark characterisation, aesthetic quantification and automated age estimation methods. Thus, facial makeup is likely to directly affect several real-life applications such as cosmetology and virtual cosmetics recommendation systems, security and access control, and social interaction. In this work, we conduct a comparative study and design automated facial makeup detection systems leveraging multiple learning schemes from a single unconstrained photograph. We have investigated and studied the efficacy of deep learning models for makeup detection incorporating the use of transfer learning strategy with semi-supervised learning using labelled and unlabelled data. First, during the supervised learning, the VGG16 convolution neural network, pre-trained on a large dataset, is fine-tuned on makeup labelled data. Secondly, two unsupervised learning methods, which are self-learning and convolutional auto-encoder, are trained on unlabelled data and then incorporated with supervised learning during semi-supervised learning. Comprehensive experiments and comparative analysis have been conducted on 2479 labelled images and 446 unlabelled images collected from six challenging makeup datasets. The obtained results reveal that the convolutional auto-encoder merged with supervised learning gives the best makeup detection performance achieving an accuracy of 88.33% and area under ROC curve of 95.15%. The promising results obtained from conducted experiments reveal and reflect the efficiency of combining different learning strategies by harnessing labelled and unlabelled data. It would also be advantageous to the beauty industry to develop such computational intelligence methods.
Current Diagnostic Methods for Assessing Transfer of Passive Immunity in Calves and Possible Improvements: A Literature Review
Authors: de Souza Rayanne Soalheiro , dos Santos Lucas Braga Costa , Melo Isabela Oliveira , Cerqueira Daiane Maria , Dumas Juliana Vieira , Leme Fabiola de Oliveira Paes , Moreira Tiago Facury , Meneses Rodrigo Melo , de Carvalho Antônio Ultimo , Facury-Filho Elias Jorge
Published: October 2021

Several direct or indirect methods can be used to assess immunoglobulin G (IgG) concentrations in calves, which evaluates the transfer of passive immunity (TPI). Radial immunodiffusion (RID) is the gold standard method to measure serum IgG in bovines. Previous studies have shown that colostrum provides several molecules in addition to immunoglobulins, which play an important role in the passive immunity of the calf. However, no studies have yet determined the level of interference of these components in the immunity, health and survival of calves. In this sense, the objective of this study is to review the methods of evaluation available for the laboratory and field diagnosis of TPI in calves and discuss the main aspects of each technique. Several methods available for TPI evaluation in calves may provide insights into the various components of colostrum involved in passive immunity.
Infection Control in the Era of COVID-19: A Narrative Review
Authors: Shbaklo Nour , Lupia Tommaso , De Rosa Francesco G. , Corcione Silvia
Published: October 2021

COVID-19 quickly became a pandemic causing millions of infections and mortalities. It required real-time adjustments to healthcare systems and infection prevention and control (IPC) measures to limit the spread and protect healthcare providers and hospitalized patients. IPC guidelines were adopted and developed based on experience gained during the MERS-CoV and SARS-CoV outbreaks. The aim of this narrative review is to summarize current evidence on IPC in healthcare settings and patients with COVID-19 to prevent nosocomial infections during the actual pandemic. A search was run on PubMed using the terms (‘COVID-19’ [Mesh]) AND (‘Infection Control’ [Mesh]) between 2019 and 2021. We identified 86 studies that were in accordance with our aim and summarized them under certain themes as they related to COVID-19 infection control measures. All the guidelines recommend early diagnosis and rapid isolation of COVID-19 patients. The necessary precautions should be taken comprising the whole process, starting with an infectious disease plan, administrative and engineering controls, triage, and PPE training. Guidelines should target modes of transmission, droplet, aerosol, and oral–fecal, while recommending control precautions. Healthcare facilities must promptly implement a multidisciplinary defense system to combat the outbreak.
FRI-1 Is an Anti-Cancer Isoquinolinequinone That Inhibits the Mitochondrial Bioenergetics and Blocks Metabolic Shifts by Redox Disruption in Breast Cancer Cells
Authors: Córdova-Delgado Miguel , Fuentes-Retamal Sebastián , Palominos Charlotte , López-Torres Camila , Guzmán-Rivera Daniela , Ramírez-Rodríguez Oney , Araya-Maturana Ramiro , Urra Félix A.
Published: October 2021

Since breast cancer (BC) cells are dependent on mitochondrial bioenergetics for promoting proliferation, survival, and metastasis, mitochondria highlight as an important target for anticancer drug discovery. FRI-1, methyl 1, 3-dimethyl-5, 8-dioxo-5, 8-dihydro-4-isoquinolinecarboxylate, was previously described as a selective cytotoxic compound on cancer cell lines, however, details on the mechanism of action remain unknown. In this work, we describe that FRI-1 inhibits mitochondrial bioenergetics, producing apoptosis in MCF7 and MDA-MB-231 BC cell lines. FRI-1 decreases the maximal oxygen consumption rate (OCR), Δψm, NADH, and ATP levels, with a notable increase of mitochondrial reactive oxygen species (ROS) production, promoting AMPK activation with pro-survival effects. Moreover, FRI-1 inhibits the metabolic remodeling to glycolysis induced by oligomycin. In isolated tumoral mitochondria, FRI-1 increases Complex I and III-dependent OCR state 2, and this is sensitive to rotenone and antimycin A inhibitor additions, suggesting a redox cycling event. Remarkably, α-ketoglutarate and lipoic acid supplementation reversed and promoted, respectively, the FRI-1-induced apoptosis, suggesting that mitochondrial redox disruption affects 2-oxoglutarate dehydrogenase (OGDH) activity, and this is involved in their anticancer mechanism. Consistent with this, the combination of FRI-1 and CPI-613, a dual inhibitor of redox-sensible tricarboxylic acid (TCA) cycle enzymes PDH and OGDH, produced extensive BC cell death. Taken together, our results suggest that FRI-1 exhibits anticancer effects through inhibition of mitochondrial bioenergetics by redox disruption in BC cells.
Detection of Pediatric Femur Configuration on X-ray Images
Authors: Drążkowska Marta
Published: October 2021

In this paper, we present a fully automatic solution for denoting bone configuration on two-dimensional images. A dataset of 300 X-ray images of children’s knee joints was collected. The strict experimental protocol established in this study increased the difficulty of post-processing. Therefore, we tackled the problem of obtaining reliable information from medical image data of insufficient quality. We proposed a set of features that unambiguously denoted configuration of the bone on the image, namely the femur. It was crucial to define the features that were independent of age, since age variability of subjects was high. Subsequently, we defined image keypoints directly corresponding to those features. Their positions were used to determine the coordinate system denoting femur configuration. A complex keypoint detector was proposed, composed of two different estimator architectures: gradient-based and based on the convolutional neural network. The positions of the keypoints were used to determine the configuration of the femur on each image frame. The overall performance of both estimators working in parallel was evaluated using X-ray images from the publicly available LERA dataset.
Universal Adversarial Attack via Conditional Sampling for Text Classification
Authors: Zhang Yu , Shao Kun , Yang Junan , Liu Hui
Published: October 2021

Despite deep neural networks (DNNs) having achieved impressive performance in various domains, it has been revealed that DNNs are vulnerable in the face of adversarial examples, which are maliciously crafted by adding human-imperceptible perturbations to an original sample to cause the wrong output by the DNNs. Encouraged by numerous researches on adversarial examples for computer vision, there has been growing interest in designing adversarial attacks for Natural Language Processing (NLP) tasks. However, the adversarial attacking for NLP is challenging because text is discrete data and a small perturbation can bring a notable shift to the original input. In this paper, we propose a novel method, based on conditional BERT sampling with multiple standards, for generating universal adversarial perturbations: input-agnostic of words that can be concatenated to any input in order to produce a specific prediction. Our universal adversarial attack can create an appearance closer to natural phrases and yet fool sentiment classifiers when added to benign inputs. Based on automatic detection metrics and human evaluations, the adversarial attack we developed dramatically reduces the accuracy of the model on classification tasks, and the trigger is less easily distinguished from natural text. Experimental results demonstrate that our method crafts more high-quality adversarial examples as compared to baseline methods. Further experiments show that our method has high transferability. Our goal is to prove that adversarial attacks are more difficult to detect than previously thought and enable appropriate defenses.
Gate Attentional Factorization Machines: An Efficient Neural Network Considering Both Accuracy and Speed
Authors: Yu Huaidong , Yin Jian , Li Yan
Published: October 2021

Nowadays, to deal with the increasing data of users and items and better mine the potential relationship between the data, the model used by the recommendation system has become more and more complex. In this case, how to ensure the prediction accuracy and operation speed of the recommendation system has become an urgent problem. Deep neural network is a good solution to the problem of accuracy, we can use more network layers, more advanced feature cross way to improve the utilization of data. However, when the accuracy is guaranteed, little attention is paid to the speed problem. We can only pursue better machine efficiency, and we do not pay enough attention to the speed efficiency of the model itself. Some models with advantages in speed, such as PNN, are slightly inferior in accuracy. In this paper, the Gate Attention Factorization Machine (GAFM) model based on the double factors of accuracy and speed is proposed, and the structure of gate is used to control the speed and accuracy. Extensive experiments have been conducted on data sets in various application scenarios, and the results show that the GAFM model is better than the existing factorization machines in both speed and accuracy.
The Role of Climate Control in Monogastric Animal Farming: The Effects on Animal Welfare, Air Emissions, Productivity, Health, and Energy Use
Authors: Costantino Andrea , Fabrizio Enrico , Calvet Salvador
Published: October 2021

In the last decades, an engineering process has deeply transformed livestock houses by introducing fine-tuned climate control systems to guarantee adequate indoor climate conditions needed to express the maximum genetic potential of animals and to increase their productivity. Climate control, hence, has strong relation with productivity but also with other livestock production domains, outlining a web of mutual relations between them. The objective of this work is to understand the actual role of climate control in intensive livestock houses by unpicking this web of mutual relations through a literature review. The results show that climate control plays a key role in intensive livestock houses since it has strong relations with animal welfare, air emissions, productivity, health, and energy use. These relations make it essential to adopt an integrated approach for the assessment of the effectiveness of any proposed improvement in the different domains of livestock production. This is especially true considering aspects such as the expected increase of livestock production in developing countries and global warming. For this purpose, integrated climate control models of livestock houses are needed, representing a challenging opportunity for performing investigations in this research field.
Backdoor Attacks to Deep Neural Network-Based System for COVID-19 Detection from Chest X-ray Images
Authors: Matsuo Yuki , Takemoto Kazuhiro
Published: October 2021

Open-source deep neural networks (DNNs) for medical imaging are significant in emergent situations, such as during the pandemic of the 2019 novel coronavirus disease (COVID-19), since they accelerate the development of high-performance DNN-based systems. However, adversarial attacks are not negligible during open-source development. Since DNNs are used as computer-aided systems for COVID-19 screening from radiography images, we investigated the vulnerability of the COVID-Net model, a representative open-source DNN for COVID-19 detection from chest X-ray images to backdoor attacks that modify DNN models and cause their misclassification when a specific trigger input is added. The results showed that backdoors for both non-targeted attacks, for which DNNs classify inputs into incorrect labels, and targeted attacks, for which DNNs classify inputs into a specific target class, could be established in the COVID-Net model using a small trigger and small fraction of training data. Moreover, the backdoors were effective for models fine-tuned from the backdoored COVID-Net models, although the performance of non-targeted attacks was limited. This indicated that backdoored models could be spread via fine-tuning (thereby becoming a significant security threat). The findings showed that emphasis is required on open-source development and practical applications of DNNs for COVID-19 detection.
The Auto-Regressive Model and Spectrum Information Entropy Judgment Method for High Intensity Focused Ultrasound Echo Signal
Authors: Yan Shang-Qu , Huang Zheng , Liu Bei , Ni Xu-Sheng , Zhang Han , Zou Xiao , Qian Sheng-You
Published: October 2021

For accurate evaluation of high intensity focused ultrasound (HIFU) treatment effect, it is of great importance to effectively judge whether the sampled signal is the HIFU echo signal or the noise signal. In this paper, a judgment method based on an auto-regressive (AR) model and spectrum information entropy is proposed. In total, 188 groups of data are obtained while the HIFU source is on or off through experiments, and these sampled signals are judged by this method. The judgment results of this method are compared with empirical judgments. It is found that when the segment number for the power spectrum estimated by AR model is 14 to 17, the judgment results of this method have a higher consistency with empirical judgments, and Accuracy, Sensitivity and Specificity all have good values. Moreover, after comparing and analyzing this method with the classic power spectrum estimation method, it is found that the recognition rate of the two sampled signals of this method is higher than that of the classic power spectrum estimation method. Therefore, this method can effectively judge the different types of sampled signals.
Oscillation of Repeated Max-Weighted Power Mean Compositions of Fuzzy Matrices
Authors: Lin Jun-Lin , Khomnotai Laksamee , Liu Hsin-Chieh
Published: October 2021

In the literature, the powers of a square fuzzy matrix with respect to the max-weighted power mean composition have been shown to always converge. This study considers the max-weighted power mean composition for a sequence of fuzzy matrices. It reveals that the repeated compositions of a sequence of n fuzzy matrices oscillate among n fuzzy matrices once the number of compositions exceeds a certain threshold. The previous finding can be considered as a special case of this study with n = 1.
Structure of Iso-Symmetric Operators
Authors: Duggal Bhagwati , Kim In-Hyoun
Published: October 2021

For a Hilbert space operator T∈B(H), let LT and RT∈B(B(H)) denote, respectively, the operators of left multiplication and right multiplication by T. For positive integers m and n, let ▵T∗,Tm(I)=(LT∗RT−I)m(I) and δT∗,Tn(I)=(LT∗−RT)m(I). The operator T is said to be (m,n)-isosymmetric if ▵T∗,TmδT∗,Tn(I)=0. Power bounded (m,n)-isosymmetric operators T∈B(H) have an upper triangular matrix representation T=T1T30T2∈B(H1⊕H2) such that T1∈B(H1) is a C0.-operator which satisfies δT1∗,T1n(I|H1)=0 and T2∈B(H2) is a C1.-operator which satisfies AT2=(Vu⊕Vb)|H2A, A=limt→∞T2∗tT2t, Vu is a unitary and Vb is a bilateral shift. If, in particular, T is cohyponormal, then T is the direct sum of a unitary with a C00-contraction.
The Curious Case of Earthworms and COVID-19
Authors: Scott-Fordsmand Janeck , Amorim Monica
Published: October 2021

Earthworms have been used for centuries in traditional medicine and are used globally as an ecotoxicological standard test species. Studies of the earthworm Eisenia fetida have shown that exposure to nanomaterials activates a primary corona-response, which is covering the nanomaterial with native proteins, the same response as to biological invaders such as a virus. We outline that the earthworm Eisenia fetida is possibly immune to COVID-19 (Severe Acute Respiratory Syndrome Coronavirus 2, SARS-CoV-2), and we describe the likely mechanisms of highly receptor-specific pore-forming proteins (PFPs). A non-toxic version of this protein is available, and we hypothesize that it is possible to use the earthworm’s PFPs based anti-viral mechanism as a therapeutic model for human SARS-CoV-2 and other corona viruses. The proteins can be used as a drug, for example, delivered with a nanoparticle in a similar way to the current COVID-19 vaccines. Obviously, careful consideration should be given to the potential risk of toxicity elicited by lysenin for in vivo usage. We aim to share this view to activate its exploration by the wider scientific community while promoting a potential therapeutic development.
Stereotactic Arrhythmia Radioablation as a Novel Treatment Approach for Cardiac Arrhythmias: Facts and Limitations
Authors: Chalkia Marina , Kouloulias Vassilis , Tousoulis Dimitris , Deftereos Spyridon , Tsiachris Dimitris , Vrachatis Dimitrios , Platoni Kalliopi
Published: October 2021

Stereotactic ablative radiotherapy (SABR) is highly focused radiation therapy that targets well-demarcated, limited-volume malignant or benign tumors with high accuracy and precision using image guidance. Stereotactic arrhythmia radioablation (STAR) applies SABR to treat cardiac arrhythmias, including ventricular tachycardia (VT) and atrial fibrillation (AF), and has recently been a focus in research. Clinical studies have demonstrated electrophysiologic conduction blockade and histologic fibrosis after STAR, which provides a proof of principle for its potential for treating arrhythmias. This review will present the basic STAR principles, available clinical study outcomes, and how the technique has evolved since the first pre-clinical study. In addition to the clinical workflow, focus will be given on the process for stereotactic radiotherapy Quality Assurance (QA) tests, as well as the need for establishing a standardized QA protocol. Future implications and potential courses of research will also be discussed.