bluuebunny/crossref_metadata_2025 huggingface dataset:
Impulsiveness indirectly affects suicidal ideation through depression and simultaneously moderates the indirect effect: A moderated mediation path model
Authors: Zhang Jingxuan , Zhang Xiaolin , Yang Guoyu , Feng Zhengzhi
Published: July 2022

Objective

This study aims to investigate the indirect effect of impulsiveness on suicidal ideation through depression and the moderating effect of impulsiveness on the indirect effect in an integrated path model.

Methods

Self-rating depression scale (SDS), Barratt impulsiveness scale-11th version (BIS-11), and self-rating idea of suicide scale (SIOSS) were applied. A moderated mediation path model was established including impulsiveness, depression, and suicidal ideation as observed variables.

Results

The main results revealed that the moderated mediation path model fit well in describing the relationships among impulsiveness, depression, and suicidal ideation. The indirect effect of impulsiveness mediated by depression and the moderating effect of impulsiveness on suicidal ideation was significant. Multiple comparisons showed that the indirect effects under different conditions of impulsiveness had statistical differences. The higher the impulsiveness was, the stronger the predictive effect of depression on suicidal ideation was.

Conclusions

The present study confirms that people who have impulsive traits are riskier to generate suicidal thoughts because they are more likely to suffer from depression and that people who are depressive have even higher risk to develop suicidal thoughts when they simultaneously have impulsive traits. In clinical and health care work, when considering depression to prevent suicidal ideation, impulsiveness needs to be monitored throughout the process of premorbid and onset stages of depression.
Attitude and Needs Toward MTM Applications of Chronic Disease in China: A Questionnaire Survey
Authors: Huang Shiqiong , Huang Juanjuan , Deng Xuanyu , Ouyang Lihui , He Gefei , Sun Ji
Published: July 2022

Objective

Chronic diseases are characterized by high incidence, long-term medication, and complex types of medication. There are also many corresponding medication therapy management (MTM) applications on the market, such as iCarea, and Medisafe. However, the existing research mainly focuses on how to choose high-quality MTM applications, and few researchers consider the expectations of MTM applications from potential users. The aims of this study were to investigate the demand, attitude, and expectations of the Chinese patients for the MTM applications to support.

Methods

From August 2019 to December 2019, we created a questionnaire to have knowledge of user needs, preferences, and expectations for MTM applications among 302 chronic patients in Hunan, Guangdong, and other provinces in China. Logistic regression analysis was performed to analyze the risk factors of affecting patients' attitudes toward MTM applications. Then, respondents' expectations and preferences for MTM applications were statistically analyzed. The survey data were merged to provide information for the design of targeted chronic disease MTM applications.

Results

A total of 260 (86.09%) out of 302 patients the respondents were willing to use the MTM applications of chronic disease. The independent influencing factors for using the MTM applications were long-term medication history (OR = 4.45, P < 0.001), willing to learn about medicine knowledge (OR = 3.01, P = 0.04), and wanting to get more professional medication knowledge via Internet (OR = 2.86, P = 0.005). It was worth noting that among those willing to use MTM applications, 55.00% of respondents were willing to use the WeChat applet for MTM, while only 23.46% of respondents preferred other applications. As to the more prevalent WeChat applet for MTM, the majority of participants expected the inclusion of useful modules, such as medication log (62.81%), medication reminder (62.81%), and medication recommendations (57.79%).

Conclusion

The participants are willing to use MTM applications of chronic disease, with a preference for the WeChat applet. Patients tended to use MTM applications if they had a long-term medication history or a desire for medical knowledge, especially if they want to get more professional medication knowledge via the Internet. Participants are expected to include in the WeChat applet as medication logs, medication reminders, and medication recommendations which should be taken into serious account for the further development of MTM applications.
Short-Term Prediction of COVID-19 Using Novel Hybrid Ensemble Empirical Mode Decomposition and Error Trend Seasonal Model
Authors: Khan Dost Muhammad , Ali Muhammad , Iqbal Nadeem , Khalil Umair , Aljohani Hassan M. , Alharthi Amirah Saeed , Afify Ahmed Z.
Published: July 2022

In this article, a new hybrid time series model is proposed to predict COVID-19 daily confirmed cases and deaths. Due to the variations and complexity in the data, it is very difficult to predict its future trajectory using linear time series or mathematical models. In this research article, a novel hybrid ensemble empirical mode decomposition and error trend seasonal (EEMD-ETS) model has been developed to forecast the COVID-19 pandemic. The proposed hybrid model decomposes the complex, nonlinear, and nonstationary data into different intrinsic mode functions (IMFs) from low to high frequencies, and a single monotone residue by applying EEMD. The stationarity of each IMF component is checked with the help of the augmented Dicky–Fuller (ADF) test and is then used to build up the EEMD-ETS model, and finally, future predictions have been obtained from the proposed hybrid model. For illustration purposes and to check the performance of the proposed model, four datasets of daily confirmed cases and deaths from COVID-19 in Italy, Germany, the United Kingdom (UK), and France have been used. Similarly, four different statistical metrics, i.e., root mean square error (RMSE), symmetric mean absolute parentage error (sMAPE), mean absolute error (MAE), and mean absolute percentage error (MAPE) have been used for a comparison of different time series models. It is evident from the results that the proposed hybrid EEMD-ETS model outperforms the other time series and machine learning models. Hence, it is worthy to be used as an effective model for the prediction of COVID-19.
Understanding the vaccine stance of Italian tweets and addressing language changes through the COVID-19 pandemic: Development and validation of a machine learning model
Authors: Cheatham Susan , Kummervold Per E. , Parisi Lorenza , Lanfranchi Barbara , Croci Ileana , Comunello Francesca , Rota Maria Cristina , Filia Antonietta , Tozzi Alberto Eugenio , Rizzo Caterina , Gesualdo Francesco
Published: July 2022

Social media is increasingly being used to express opinions and attitudes toward vaccines. The vaccine stance of social media posts can be classified in almost real-time using machine learning. We describe the use of a Transformer-based machine learning model for analyzing vaccine stance of Italian tweets, and demonstrate the need to address changes over time in vaccine-related language, through periodic model retraining. Vaccine-related tweets were collected through a platform developed for the European Joint Action on Vaccination. Two datasets were collected, the first between November 2019 and June 2020, the second from April to September 2021. The tweets were manually categorized by three independent annotators. After cleaning, the total dataset consisted of 1,736 tweets with 3 categories (promotional, neutral, and discouraging). The manually classified tweets were used to train and test various machine learning models. The model that classified the data most similarly to humans was XLM-Roberta-large, a multilingual version of the Transformer-based model RoBERTa. The model hyper-parameters were tuned and then the model ran five times. The fine-tuned model with the best F-score over the validation dataset was selected. Running the selected fine-tuned model on just the first test dataset resulted in an accuracy of 72.8% (F-score 0.713). Using this model on the second test dataset resulted in a 10% drop in accuracy to 62.1% (F-score 0.617), indicating that the model recognized a difference in language between the datasets. On the combined test datasets the accuracy was 70.1% (F-score 0.689). Retraining the model using data from the first and second datasets increased the accuracy over the second test dataset to 71.3% (F-score 0.713), a 9% improvement from when using just the first dataset for training. The accuracy over the first test dataset remained the same at 72.8% (F-score 0.721). The accuracy over the combined test datasets was then 72.4% (F-score 0.720), a 2% improvement. Through fine-tuning a machine-learning model on task-specific data, the accuracy achieved in categorizing tweets was close to that expected by a single human annotator. Regular training of machine-learning models with recent data is advisable to maximize accuracy.
Perceived Effects of COVID-19 Pandemic on Food Security in Southeast Nigeria
Authors: Munonye Jane , Osuji Emeka , Olaolu Michael , Okoisu Anthony , Obi Joy , Eze Gladys , Ibrahim-Olesin Sikiru , Njoku Loveday , Amadi Mark , Izuogu Chibuzo , Azuamairo Gillian
Published: July 2022

The present study evaluated the perceived effects of the COVID-19 Pandemic on food security in Southeast Nigeria. A multi-stage random technique was used to select 209 households. Data for the study were collected with the aid of a structured questionnaire and were analyzed using descriptive statistics, z-test, food security model, and Tobit regression model. Results showed that the mean household size was 9.6 persons, which indicates a large household size. The percentage rate of food consumption of the households before the Pandemic was higher relative to the COVID-19 event. Again, exorbitant prices of food materials were noticed during the COVID-19 as compared to the period before the Pandemic. About 10.5% of the households met the minimum food requirements as proposed by World Health Organization (WHO), and Food and Agriculture Organization (FAO) as against the majority of 76.1%. The three dimensions of food security which include availability, accessibility, and utilization were interposed by a number of factors, such as artificial scarcity, and an increase in food prices. Furthermore, social distancing and lockdown imposition were COVID-19 determinants of the food security status of households in the Southeast Nigeria. About 24% of the households were food-secured compared to 76% that were insecured during the Pandemic. Robust and effective food and agricultural policy formulations and implementations were recommended in Southeast Nigeria.
Development of an equation to screen for solar hemorrhages from digital cushion ultrasound texture analysis in veal calves at slaughter
Authors: Fabbri Giorgia , Magrin Luisa , Gottardo Flaviana , Armato Leonardo , Contiero Barbara , Gianesella Matteo , Fiore Enrico
Published: July 2022

Claw disorders are a relevant welfare issue in the cattle industry, fast and accurate diagnoses are essential for successful treatment and prevention. The present study aimed to develop an equation to assess the presence of solar hemorrhages from real-time ultrasound images texture analysis at slaughter. Eighty-eight hind feet were collected at the slaughterhouse from 44 Holstein male veal calves. The claws were trimmed by a veterinarian hoof-trimmer, approximately 30 min after the calves' slaughter, and classified into healthy and affected by solar hemorrhages. At the same time, ultrasound images were collected for each claw. Sole soft tissues' thickness was measured, and texture analysis was performed using MaZda software. The resulting parameters from sole soft tissues' measurements and texture analysis were screened with a stepwise linear discriminant analysis using the absence or presence (0/1) of solar hemorrhages as the dependent variable. Results from the stepwise analysis identified 9 variables (among 279) as predictors, and an equation was developed and used to predict the presence or absence of solar hemorrhages on the scanned claws by binary measure: values ≤0.5 counted as 0, while those >0.5 as 1. Validation of the equation was performed by testing predicted lesions (LESpred) against the clinically evaluated lesions (LESeval) with a confusion matrix, a ROC analysis, and a precision-recall curve. Results of the present study suggest that the equation proposed has a good potential for detecting effectively hemorrhages of the sole by ultrasound imaging texture means, and could be used to monitor unsatisfactory housing and management conditions at the farm level, and for early management intervention and prevention.
Comparative analysis of differentially abundant proteins between high and low intramuscular fat content groups in donkeys
Authors: Tan Xiaofan , He Yu , Qin Yanchun , Yan Zhiwei , Chen Jing , Zhao Ruixue , Zhou Shenglan , Irwin David M. , Li Bojiang , Zhang Shuyi
Published: July 2022

Intramuscular fat (IMF) is an important regulator that determines meat quality, and its content is closely related to flavor, tenderness, and juiciness. Many studies have used quantitative proteomic analysis to identify proteins associated with meat quality traits in livestock, however, the potential candidate proteins that influence IMF in donkey muscle are not fully understood. In this study, we performed quantitative proteomic analysis, with tandem-mass-tagged (TMT) labeling, with samples from the longissimus dorsi (LD) muscle of the donkey. A total of 585,555 spectra were identified from the six muscle samples used in this study. In total, 20,583 peptides were detected, including 15,279 unique peptides, and 2,540 proteins were identified. We analyzed differentially abundant proteins (DAPs) between LD muscles of donkeys with high (H) and low (L) IMF content. We identified 30 DAPs between the H and L IMF content groups, of which 17 were upregulated and 13 downregulated in the H IMF group. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis of these DAPs revealed many GO terms (e.g., bone morphogenetic protein (BMP) receptor binding) and pathways (e.g., Wnt signaling pathway and Hippo signaling pathway) involved in lipid metabolism and adipogenesis. The construction of protein–protein interaction networks identified 16 DAPs involved in these networks. Our data provide a basis for future investigations into candidate proteins involved in IMF deposition and potential new approaches to improve meat quality in the donkey.
A framework for non-preserved consensus gene module detection in Johne's disease
Authors: Heidari Maryam , Pakdel Abbas , Bakhtiarizadeh Mohammad Reza , Dehghanian Fariba
Published: July 2022

Johne's disease caused by Mycobacterium avium subsp. paratuberculosis (MAP) is a major concern in dairy industry. Since, the pathogenesis of the disease is not clearly known, it is necessary to develop an approach to discover molecular mechanisms behind this disease with high confidence. Biological studies often suffer from issues with reproducibility. Lack of a method to find stable modules in co-expression networks from different datasets related to Johne's disease motivated us to present a computational pipeline to identify non-preserved consensus modules. Two RNA-Seq datasets related to MAP infection were analyzed, and consensus modules were detected and were subjected to the preservation analysis. The non-preserved consensus modules in both datasets were determined as they are modules whose connectivity and density are affected by the disease. Long non-coding RNAs (lncRNAs) and TF genes in the non-preserved consensus modules were identified to construct integrated networks of lncRNA-mRNA-TF. These networks were confirmed by protein-protein interactions (PPIs) networks. Also, the overlapped hub genes between two datasets were considered hub genes of the consensus modules. Out of 66 consensus modules, 21 modules were non-preserved consensus modules, which were common in both datasets and 619 hub genes were members of these modules. Moreover, 34 lncRNA and 152 TF genes were identified in 12 and 19 non-preserved consensus modules, respectively. The predicted PPIs in 17 non-preserved consensus modules were significant, and 283 hub genes were commonly identified in both co-expression and PPIs networks. Functional enrichment analysis revealed that eight out of 21 modules were significantly enriched for biological processes associated with Johne's disease including “inflammatory response,” “interleukin-1-mediated signaling pathway”, “type I interferon signaling pathway,” “cytokine-mediated signaling pathway,” “regulation of interferon-beta production,” and “response to interferon-gamma.” Moreover, some genes (hub mRNA, TF, and lncRNA) were introduced as potential candidates for Johne's disease pathogenesis such asTLR2, NFKB1, IRF1, ATF3, TREM1, CDH26, HMGB1, STAT1, ISG15, CASP3. This study expanded our knowledge of molecular mechanisms involved in Johne's disease, and the presented pipeline enabled us to achieve more valid results.
The Exogenous Application of Brassinosteroids Confers Tolerance to Heat Stress by Increasing Antioxidant Capacity in Soybeans
Authors: Wang Weiling , Xie Yuncan , Liu Chang , Jiang Haidong
Published: July 2022

Heat stress is an important factor affecting soybean yield. Brassinosteroids (BRs) play a crucial role in plant growth, development, and defense. In the present study, the regulatory effects of 24-epibrassinolide (EBR, one of the bioactive BRs) on heat tolerance in soybeans, and its underlying physiological mechanisms were investigated. The results show that foliar spraying with EBR significantly alleviate heat stress-induced water loss and oxidative damage in soybean leaves. The activities of antioxidant enzymes (superoxide dismutase, catalase, and peroxidase) and the contents of antioxidant substances (ascorbic acid and reduced glutathione) were markedly increased in EBR-treated leaves compared with water-treated leaves, which contributed to maintaining reactive oxygen species homeostasis and relieving oxidative injury under heat stress. However, EBR-treated leaves showed a significant decrease in free proline and total soluble sugar content under heat stress compared to water-treated leaves. In addition, EBR treatment showed obviously higher photosystem II activity under heat stress, and higher net photosynthetic rate and biomass accumulation after recovery from heat stress compared to water treatment. Collectively, these results indicated that EBR could significantly improve the capacity of antioxidant defense systems to protect photosynthetic apparatus under heat stress, thereby effectively alleviating heat stress-induced growth inhibition in soybean plants.
Spatiotemporal Change of Heat Stress and Its Impacts on Rice Growth in the Middle and Lower Reaches of the Yangtze River
Authors: Zhang Shuai
Published: July 2022

Heat stress will restrict rice yield in the middle and lower reaches of the Yangtze River. An understanding of the meteorological conditions of heat stress of rice production is important for improving the accuracy of the phenology simulation. Based on the observations of phenology and heat stress of rice agrometeorological stations in this region, as well as meteorological observations and future scenarios, this study analyzed the spatiotemporal change of heat stress and its impacts on rice growth in this region from 1990 to 2009. The results showed that the heat stress frequency of early rice increased in this region from 2000 to 2009, and that of late rice and single-season rice decreased. Moreover, rice phenology will advance under heat stress conditions. The spatiotemporal consistency of the observations and the meteorological index of heat stress shows that the change in heat stress is attributed to climate changes and extreme meteorological events. Under future climate scenarios, it is found that the frequency of heat stress will increase, which will have a serious impact on rice production. The results suggest that positive and effective measures should be taken to adapt to climate change for rice production.
Important Mycosis of Wildlife: Emphasis on Etiology, Epidemiology, Diagnosis, and Pathology—A Review: PART 2
Authors: Ugochukwu Iniobong Chukwuebuka Ikenna , Luca Iasmina , Sani Nuhu Abdulazeez , Omeke Jacinta Ngozi , Anyanwu Madubuike Umunna , Odigie Amienwanlen Eugene , Onoja Remigius Ibe , Ocheja Ohiemi Benjamin , Ugochukwu Miracle Oluchukwu , Makanju Olabisi Aminah , Aneke Chioma Inyang
Published: July 2022

Wild animals are an important component of the ecosystem, and play a major role in it. However, in recent years, there has been an astronomical increase in the incidence of wildlife mycotic diseases leading to wildlife extermination. It is important to note that most of these mycotic diseases are zoonotic, and since there is a lot of attention given to zoonosis of a bacterial or viral origin in recent times, it is important to look into the mycotic diseases which may have zoonotic potential. Previously, the authors expatiated on some major wildlife mycotic diseases. In this review, we shed light on the etiology, epidemiology, diagnosis, pathogenesis, pathogenicity, macroscopic and microscopic pathology, and hematological and serum biochemical findings of dermatophytosis, coccidioidomycosis, blastomycosis, and sporotrichosis, which are very important mycoses of wildlife.
Relay Intercropping Winter Cover Crop Effects on Spring Forage Potential of Sweet Maize Stover and Yearling Cattle Beef Performance
Authors: Lauriault Leonard M. , Guldan Steven J. , Popiel-Powers Fernanda G. , Steiner Robert L. , Martin Charles A. , Falk Constance L. , Petersen Mark K. , May Tammy
Published: July 2022

Small landholders who grow sweet maize for the fresh produce market often also have cattle with little access to winter forage. Grazing cover crops with sweet maize stover can potentially increase the available nutritive value. A 3-year randomized complete block study with three replicates at New Mexico State University’s Alcalde Sustainable Agriculture Science Center compared sweet maize (Zea mays var. rugosa) with sweet maize relay intercropped at the V7–9 stage with cereal rye (rye: Secale cereale L.) or hairy vetch (vetch: Vicia villosa Roth) for early spring grazing. Intercropping the rye or hairy vetch into sweet maize did not influence the sweet maize stover biomass yield or nutritive value after the winter. The dry matter (DM) yield and crude protein (CP) concentration of hairy vetch biomass was greater (p < 0.01) than rye biomass (1.46 vs. 2.94 Mg DM ha−1 for rye and hairy vetch, respectively, and 145 vs. 193 g CP kg−1 for rye and hairy vetch, respectively). Average daily gains by yearling cattle were not different when grazing maize–rye or maize–vetch. Producers should consider the spring planting timing of the primary crop and the initiation of grazing in the winter or the spring to maximize the utilization of the previous crop’s residue (stover), as well as the cover crop itself.
Growth Performance, Histological Changes and Functional Tests of Broiler Chickens Fed Diets Supplemented with Tribulus Terrestris Powder
Authors: Al-Garadi Maged A. , Al-Baadani Hani H. , Alqhtani Abdulmohsen H.
Published: July 2022

The current experiment aimed to investigate the effects of TT powder on performance parameters and functional tests, as well as on morphological and histological changes in the liver, kidney and ileum in broiler chickens. Commercial broilers (total = 168 females) were used, equally divided into three dietary treatments (C = 0.0, T1 = 0.75, and T2 = 1.5 g/kg diet). The growth performance (1–35 days of age), absolute and relative weight, liver and kidney functional tests, intestinal morphology (14 and 35 days of age), and histomorphology of the ileum (35 days of age) were evaluated. At 35 days of age, histopathological changes in the ileum, liver, and kidney were also examined. The results showed that the growth performance and absolute and relative weights of the liver and kidney had no negative effects when dietary supplementation with TT powder was given at 0.75 g/kg diet (T1), whereas a decrease was observed at T2 (p < 0.05). Liver and kidney functional tests showed no significant effects in all feed treatments (14 days), while T1 showed lower (p < 0.05) ALT and AST levels (35 days). T1 exhibited higher weights, lengths, and weight-to-length ratios of the small intestine, and relative lengths of the duodenum (p < 0.05). Histomorphometric measurements of the ileum were higher (p < 0.05) in chickens fed the 0.75 g TT/kg diet, and except for in the goblet cell count and epithelial thickness, there were no differences between treatments (p > 0.05). In T1, hepatocytes were more normal but hepatic sinusoids were dilated, whereas in T2, lymphocytes had infiltrated around the central vein and lining endothelial cells had been lost. The kidney was improved in T1 and T2 compared with the control group. Ileal villi were shorter in T2, and some villi fused with enterocyte necrosis and inflammatory cells accumulated in the lumen. We concluded that TT powder (0.75 g/kg feed) has a safe effect and is healthy for broilers.
Household Rituals and Merchant Caravanners: The Phenomenon of Early Bronze Age Donkey Burials from Tell eṣ-Ṣâfi/Gath, Israel
Authors: Greenfield Haskel J. , Ross Jon , Greenfield Tina L. , Albaz Shira , Richardson Sarah J. , Maeir Aren M.
Published: July 2022

Most studies of ritual and symbolism in early complex societies of the Near East have focused on elite and/or public behavioural domains. However, the vast bulk of the population would not have been able to fully participate in such public displays. This paper explores the zooarchaeological and associated archaeological evidence for household rituals in lower-stratum residences in the Early Bronze Age (EB) of the southern Levant. Data from the EB III (c. 2850–2550 BCE) deposits excavated at the site of Tell eṣ-Ṣâfi/Gath, Israel, are illustrative of the difficulty in identifying the nature of household rituals. An integrated analytical approach to the architecture, figurines, foundation deposits, and domestic donkey burials found in lower-stratum domestic residences provides insights into the nature of household rituals. This integrated contextual perspective allows the sacred and symbolic role(s) of each to be understood and their importance for EB urban society to be evaluated.
Special Issue “Thermochemical Conversion Processes for Solid Fuels and Renewable Energies: Volume II”
Authors: Alobaid Falah , Ströhle Jochen , Epple Bernd
Published: July 2022

The increasing share of renewable energy sources draws attention to a critical challenge [...]
Plant Photochemistry under Glass Coated with Upconversion Luminescent Film
Authors: Yanykin Denis V. , Paskhin Mark O. , Simakin Alexander V. , Burmistrov Dmitriy E. , Pobedonostsev Roman V. , Vyatchinov Alexey A. , Vedunova Maria V. , Kuznetsov Sergey V. , Ermakova Julia A. , Alexandrov Alexander A. , Glinushkin Alexey P. , Kalinitchenko Valery P. , Khayrullin Mars , Kuznetsova Elena , Dubinin Mikhail V. , Kozlov Valery A. , Bunkin Nikolai F. , Sibirev Alexey V. , Aksenov Alexander G. , Gudkov Sergey V.
Published: July 2022

It has been shown that the cultivation of plants under glass coated with nano-sized upconversion luminophores led to an increase in plant productivity and the acceleration of plant adaptation to ultraviolet radiation. In the present work, we examined the effect of upconversion nanopowders with the nominal composition Sr0.955Yb0.020Er0.025F2.045 on plant (Solanum lycopersicum) photochemistry. The composition, structure and size of nanoparticles were tested using X-ray pattern diffraction, scanning electron microscopy, and dynamic light scattering. Nanoparticles are capable of converting infrared radiation into red and green photons. Glasses coated with upconversion luminophores increase the intensity of photosynthetically active radiation and absorb the ultraviolet and far-red radiation. The chlorophyll a fluorescence method showed that plants growing under photoconversion and those growing under common film demonstrate different ability to utilize excitation energy via photosynthesis. It was shown that under ultraviolet and high light conditions, the efficiency of the photochemical reactions, the non-photochemical fluorescence quenching, and the electron transport remained relatively stable in plants growing under photoconversion film in contrast to plants growing under common film. Thus, cultivation of Solanum lycopersicum under photoconversion glasses led to the acceleration in plant growth due to greater efficiency of plant photochemistry under stress conditions.
The Gap between the Admitted and the Measured Technical Debt: An Empirical Study
Authors: Pavlič Luka , Hliš Tilen , Heričko Marjan , Beranič Tina
Published: July 2022

Technical debt is a well understood and used concept in IT development. The metaphor, rooted in the financial world, captures the amount of work that development teams owe to a product. Every time developers take a shortcut within development, the technical debt accumulates. Technical debt identification can be accomplished via manual reporting on the technical debt items, which is called self-admitted technical debt. Several specialised methods and tools have also emerged that promise to measure the technical debt. Based on experience in the community, the impression emerged that the measured technical debt is of a significantly different amount than the self-admitted debt. In this context, we decided to perform empirical research on the possible gap between the two. We investigated 14 production-grade software products while determining the amount of accumulated technical debt via (a) a self-admitting procedure and (b) measuring the debt. The outcomes show clearly the significant difference in the technical debt reported by the two methods. We urge development and quality-assurance teams not to rely on technical debt measurement alone. The tools demonstrated their strength in identifying low-level code technical debt items that violate a set of predefined rules. However, developers should have additional insight into violations, based on the interconnected source code and its relation to the domain and higher-level design decisions.
Experimental Measurements and Numerical Simulation of H2S Generation during Cyclic Steam Stimulation Process of Offshore Heavy Oil from Bohai Bay, China
Authors: Wang Taichao , Yang Renfeng , Zhang Lijun , Zheng Wei , Sun Yan , Bai Yuting
Published: July 2022

Cyclic steam stimulation (CSS) is successfully applied to increase heavy oil recovery in heavy oil reservoirs in Bohai Bay, China. However, during the CSS processes, hydrogen sulfide (H2S) was detected in some heavy oil reservoirs. The existing literature mainly focused on the H2S generation of onshore heavy oil. There is no concrete experimental data available, especially about the level of H2S generation during CSS of offshore heavy oil. In addition, there is still a lack of effective reaction kinetic models and numerical simulation methods to simulate H2S generation during the CSS of offshore heavy oil. Therefore, this paper presents a case study from Bohai Bay, China. First, the laboratory aquathermolysis tests were conducted to simulate the gases that are produced during the CSS processes of heavy oil. The effects of the reaction temperature and time on the H2S generation were studied. Then, a one-dimensional CSS experiment was performed to predict H2S generation under reservoir conditions. A kinetic model for the prediction of H2S generation during the CSS of heavy oil was presented. The developed model was calibrated with the experimental data of the one-dimensional CSS experiment at a temperature of 300 °C. Finally, a reservoir model was developed to predict H2S generation and investigate the effects of soaking time, steam quality, and steam injection volume on H2S generation during CSS processes. The results show that the H2S concentration increased from 0.77 ppm in the first cycle to 1.94 ppm in the eighth cycle during the one-dimensional CSS experiment. The average absolute error between the measured and simulated H2S production was 12.46%, indicating that the developed model can accurately predict H2S production. The H2S production increase with soaking time, steam quality, and steam injection volume due to the strengthened aquathermolysis reaction. Based on the reservoir simulation, the H2S production was predicted in the range of 228 m3 to 2895 m3 within the parameters of this study.
Neural Networks for Early Diagnosis of Postpartum PTSD in Women after Cesarean Section
Authors: Orovas Christos , Orovou Eirini , Dagla Maria , Daponte Alexandros , Rigas Nikolaos , Ougiaroglou Stefanos , Iatrakis Georgios , Antoniou Evangelia
Published: July 2022

The correlation between the kind of cesarean section and post-traumatic stress disorder (PTSD) in Greek women after a traumatic birth experience has been recognized in previous studies along with other risk factors, such as perinatal conditions and traumatic life events. Data from early studies have suggested some possible links between some vulnerable factors and the potential development of postpartum PTSD. The classification of each case in three possible states (PTSD, profile PTSD, and free of symptoms) is typically performed using the guidelines and the metrics of the version V of the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) which requires the completion of several questionnaires during the postpartum period. The motivation in the present work is the need for a model that can detect possible PTSD cases using a minimum amount of information and produce an early diagnosis. The early PTSD diagnosis is critical since it allows the medical personnel to take the proper measures as soon as possible. Our sample consists of 469 women who underwent emergent or elective cesarean delivery in a university hospital in Greece. The methodology which is followed is the application of random decision forests (RDF) to detect the most suitable and easily accessible information which is then used by an artificial neural network (ANN) for the classification. As is demonstrated from the results, the derived decision model can reach high levels of accuracy even when only partial and quickly available information is provided.
Limb Laterality Discrimination, Evoked Sensations and Somatosensory Behavior in Fibromyalgia Syndrome: A Cross-Sectional Study
Authors: Riquelme-Aguado Víctor , Gil-Crujera Antonio , Fernández-Carnero Josué , Cuenca-Martínez Ferran , Gómez Esquer Francisco
Published: July 2022

The main objective of this study was to assess the status of body schema using limb laterality discrimination tasks and pain measurement variables of patients with FMS compared to healthy subjects. The secondary aim was to analyze the relationships between laterality discrimination with respect to somatosensory variables. Thirty female patients with FMS (with a mean age of 52.43 ± 11.82 years) and thirty healthy women (with a mean age of 47.93 ± 5.92 years) were recruited. The main outcome measures were laterality discrimination, referral of evoked sensations, pressure pain threshold and conditioned pain modulation. The main analysis showed that patients with FMS have a longer reaction time for laterality discrimination in hands (hands—20 images, t = 4.044, p < 0.0001, d = 1.04; hands—50 images t = 4.012, p < 0.0001, d = 1.31; feet—20 images t = 2.982, p < 0.01, d = 0.76; feet—50 images, t = 2.159, p < 0.05, d = 0.55). With regard the secondary analysis, patients with FM have higher mechanical hyperalgesia (t = −9.550; p < 0.0001, d = 2.51) and decreased response to conditioned pain modulation compared with healthy subjects (t = 15.519; p < 0.0001, d = 4.17). A positive correlation was found in patients with FMS between greater laterality discrimination ability and better function of conditioned pain modulation (hands r = 0.676, p < 0.0001; feet r = 0.485, p < 0.01). In conclusion, patients with FMS have a longer reaction time and lower accuracy for laterality discrimination, increased mechanical hyperalgesia and decreased conditioned pain modulation compared to healthy subjects. Finally, it seems that there is a positive correlation between greater laterality discrimination ability and better conditioned pain modulation function.
Big Data ETL Process and Its Impact on Text Mining Analysis for Employees’ Reviews
Authors: Tanasescu Laura Gabriela , Vines Andreea , Bologa Ana Ramona , Vaida Claudia Antal
Published: July 2022

Big data analysis is challenging in the current context for enterprises that would like to apply these capabilities in the human resource sector. This paper will show how an organization can take advantage of the current or former employees’ reviews that are provided on a constant basis on different sites, so that the management can adjust or change business decisions based on employees’ wishes, dissatisfaction or needs. Considering the previously mentioned challenge on big data analysis, this research will first provide the best practice for the collection and transformation of the data proposed for analysis. The second part of this paper presents the extraction of two datasets containing employee reviews using data scraping techniques, the analysis of data by using text mining techniques to retrieve business insights and the comparison of the results for these algorithms. Experimental results with Naïve Bayes, Logistic Regression, K-Nearest Neighbor and Support Vector Machine for employee sentiment prediction showed much better performances for Logistic Regression. Three out of the four analyzed algorithms performed better for the second, triple-size dataset. The final aim of the paper is to provide an end-to-end solution with high performance and reduced costs.
Image Processing and Analysis for Preclinical and Clinical Applications
Authors: Stefano Alessandro , Vernuccio Federica , Comelli Albert
Published: July 2022

Preclinical and clinical imaging aims to characterize and measure biological processes and diseases in animals [...]
Phosphine Fumigation Followed by Cold Treatment to Control Peach Fruit Moth, Carposina sasakii, Larvae on “Fuji” Apples Intended for Export
Authors: Kim Bong-Su , Hong Ki-Jeong , Kwon Tae-Hyung , Lee Kyeong-Yeoll , Lee Byung-Ho , Lee Sung-Eun
Published: July 2022

The fumigation of apples using methyl bromide (MeBr) can cause severe deterioration in fruit quality. Moreover, maintaining the quality of apples during postharvest storage and eradicating pests, especially those involved in quarantine issues, are important for facilitating the export of apples, including the “Fuji” apple (Malus pumila var. “Fuji”) in South Korea. In the present study, phosphine (PH3) fumigation as an alternative to MeBr was found to be more effective for the control of peach fruit moth larvae (Carposina sasakii), which had naturally infested Fuji apples, at a high temperature (25 °C) rather than at a low temperature (5 °C). To achieve the industry requirement of better-quality perishable commodities and meet quarantine guidelines for export, PH3 fumigation at the low temperature (5 °C) was followed by cold treatments at 3 ± 2 °C for 2 and 4 weeks, which led to higher efficacy than was achieved using PH3 at 5 °C alone. Given that chemical treatments, such as treatment with 1-methylcyclopropene, can inhibit ethylene synthesis, low-temperature PH3 fumigation for 72 h followed by 4 weeks of cold treatment could also extend the shelf life of apples and resolve known quarantine issues when used as an alternative to MeBr treatment.
Breast Lesions Screening of Mammographic Images with 2D Spatial and 1D Convolutional Neural Network-Based Classifier
Authors: Lin Chia-Hung , Lai Hsiang-Yueh , Chen Pi-Yun , Wu Jian-Xing , Pai Ching-Chou , Su Chun-Min , Ho Hui-Wen
Published: July 2022

Mammography is a first-line imaging examination that employs low-dose X-rays to rapidly screen breast tumors, cysts, and calcifications. This study proposes a two-dimensional (2D) spatial and one-dimensional (1D) convolutional neural network (CNN) to early detect possible breast lesions (tumors) to reduce patients’ mortality rates and to develop a classifier for use in mammographic images on regions of interest where breast lesions (tumors) may likely occur. The 2D spatial fractional-order convolutional processes are used to strengthen and sharpen the lesions’ features, denoise, and improve the feature extraction processes. Then, an automatic extraction task is performed using a specific bounding box to sequentially pick out feature patterns from each mammographic image. The multi-round 1D kernel convolutional processes can also strengthen and denoise 1D feature signals and assist in the identification of the differentiation levels of normality and abnormality signals. In the classification layer, a gray relational analysis-based classifier is used to screen the possible lesions, including normal (Nor), benign (B), and malignant (M) classes. The classifier development for clinical applications can reduce classifier’s training time, computational complexity level, computational time, and achieve a more accurate rate for meeting clinical/medical purpose. Mammographic images were selected from the mammographic image analysis society image database for experimental tests on breast lesions screening and K-fold cross-validations were performed. The experimental results showed promising performance in quantifying the classifier’s outcome for medical purpose evaluation in terms of recall (%), precision (%), accuracy (%), and F1 score.
Post-Authorship Attribution Using Regularized Deep Neural Network
Authors: Modupe Abiodun , Celik Turgay , Marivate Vukosi , Olugbara Oludayo
Published: July 2022

Post-authorship attribution is a scientific process of using stylometric features to identify the genuine writer of an online text snippet such as an email, blog, forum post, or chat log. It has useful applications in manifold domains, for instance, in a verification process to proactively detect misogynistic, misandrist, xenophobic, and abusive posts on the internet or social networks. The process assumes that texts can be characterized by sequences of words that agglutinate the functional and content lyrics of a writer. However, defining an appropriate characterization of text to capture the unique writing style of an author is a complex endeavor in the discipline of computational linguistics. Moreover, posts are typically short texts with obfuscating vocabularies that might impact the accuracy of authorship attribution. The vocabularies include idioms, onomatopoeias, homophones, phonemes, synonyms, acronyms, anaphora, and polysemy. The method of the regularized deep neural network (RDNN) is introduced in this paper to circumvent the intrinsic challenges of post-authorship attribution. It is based on a convolutional neural network, bidirectional long short-term memory encoder, and distributed highway network. The neural network was used to extract lexical stylometric features that are fed into the bidirectional encoder to extract a syntactic feature-vector representation. The feature vector was then supplied as input to the distributed high networks for regularization to minimize the network-generalization error. The regularized feature vector was ultimately passed to the bidirectional decoder to learn the writing style of an author. The feature-classification layer consists of a fully connected network and a SoftMax function to make the prediction. The RDNN method was tested against thirteen state-of-the-art methods using four benchmark experimental datasets to validate its performance. Experimental results have demonstrated the effectiveness of the method when compared to the existing state-of-the-art methods on three datasets while producing comparable results on one dataset.
Gloss and Modelling Studies of Stone Polishing Using Linear Polishing Machines with Rotating Heads
Authors: Coelho Adriano , Pereira José Carlos Garcia , Amaral Pedro M. , Rosa Luís Guerra
Published: July 2022

The ornamental stone industry has always played an important role in the world economy. Polishing the slabs to increase their gloss is important to enhance the beauty and richness of these natural materials. Many industrial polishing machines rely on a rotating head’s movement along zigzag trajectories (controlled by belt, transverse and rotational speeds), to erode the surface as stochastically as possible (to avoid scratches and other visual defects caused by paths that are too symmetrical). Optimizing (and automatizing) these three speeds together therefore represents a significant gain for the industry, in time, energy, and quality of product. In this work we show that this optimization can be accomplished by fulfilling these conditions: (1) the displacement of the polishing head after a single zigzag movement should be smaller than its diameter; and (2) the displacement of the polishing head after a single rotation should be smaller than its radius. To assess the validity of these two conditions, we studied the polishing activity using experiments based on gloss measurements of the polished stone and computer simulations based on the geometric contacts between the tool and the stone. We concluded that: (i) a clear correlation can be established between experimental and simulation data; (ii) the two displacement parameters represent an effective way to control the quality and efficiency of the polishing process; and (iii) there is a limit to the gloss acquired through polishing processes, thus polishing above a given threshold decreases the efficiency without increasing the quality. The correspondence between experimental and modelling results opens the door to further optimizations of these polishing processes in the future.
B Cell Subsets in Colombian Adults with Predominantly Antibody Deficiencies, Bronchiectasis or Recurrent Pneumonia
Authors: Giraldo-Ocampo Sebastian , Bonelo Anilza , Zea-Vera Andres F.
Published: July 2022

Aim: To evaluate and describe lymphocyte populations’ and B cell subsets’ frequencies in patients presenting with Predominantly antibody deficiencies (PAD) and diagnosed with bronchiectasis or recurrent pneumonia seen in Cali (Colombian Southwest region). Materials and Methods: 16 subjects with PAD, 20 subjects with pulmonary complications (bronchiectasis or recurrent pneumonia) and 20 healthy donors (HD). Controls and probands between 14 and 64 years old, regardless of gender were included. Lymphocyte populations (T, B and NK cells) and B cell subsets were evaluated in peripheral blood mononuclear cells using flow cytometry, T/B/NK reagent and the pre-germinal center antibody panel proposed by the EUROflow consortium were used. EUROclass and the classification proposed by Driessen et al. were implemented. Results: CVID patients exhibited increase absolute numbers of CD8+ T cells and reduce NK cells as compare with HD, other PAD cases or pulmonary complications. PAD B cell subsets were disturbed when compared to the age range-matched healthy donors. Among B cell subsets, the memory B cell compartment was the most affected, especially switched memory B cells. Four participants were classified as B- and two CVID as smB-Trnorm and smB-21low groups according to EUROclass classification. The most frequent patterns proposed by Driessen et al. were B cell production and germinal center defect. Conclusions: B cell subsets, especially memory B cells, are disturbed in PAD patients from Southwestern Colombia. To the best of our knowledge this is the most comprehensive study of B cell subsets in Colombian adults.