bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative Sensitivity and Specificity of the 7SL sRNA Diagnostic Test for Animal Trypanosomiasis
Authors: Contreras Garcia Maria , Walshe Emily , Steketee Pieter C. , Paxton Edith , Lopez-Vidal Javier , Pearce Michael C. , Matthews Keith R. , Ezzahra-Akki Fatima , Evans Alec , Fairlie-Clark Karen , Matthews Jacqueline B. , Grey Finn , Morrison Liam J.
Published: April 2022

Animal trypanosomiasis (AT) is a significant livestock disease, affecting millions of animals across Sub-Saharan Africa, Central and South America, and Asia, and is caused by the protozoan parasites Trypanosoma brucei, Trypanosoma vivax, and Trypanosoma congolense, with the largest economic impact in cattle. There is over-reliance on presumptive chemotherapy due to inadequate existing diagnostic tests, highlighting the need for improved AT diagnostics. A small RNA species, the 7SL sRNA, is excreted/secreted by trypanosomes in infected animals, and has been previously shown to reliably diagnose active infection. We sought to explore key properties of 7SL sRNA RT-qPCR assays; namely, assessing the potential for cross-reaction with the widespread and benign Trypanosoma theileri, directly comparing assay performance against currently available diagnostic methods, quantitatively assessing specificity and sensitivity, and assessing the rate of decay of 7SL sRNA post-treatment. Results showed that the 7SL sRNA RT-qPCR assays specific for T. brucei, T. vivax, and T. congolense performed better than microscopy and DNA PCR in detecting infection. The 7SL sRNA signal was undetectable or significantly reduced by 96-h post treatment; at 1 × curative dose there was no detectable signal in 5/5 cattle infected with T. congolense, and in 3/5 cattle infected with T. vivax, with the signal being reduced 14,630-fold in the remaining two T. vivax cattle. Additionally, the assays did not cross-react with T. theileri. Finally, by using a large panel of validated infected and uninfected samples, the species-specific assays are shown to be highly sensitive and specific by receiver operating characteristic (ROC) analysis, with 100% sensitivity (95% CI, 96.44–100%) and 100% specificity (95% CI, 96.53–100%), 96.73% (95% CI, 95.54–99.96%) and 99.19% specificity (95% CI, 92.58–99.60%), and 93.42% (95% CI, 85.51–97.16% %) and 82.43% specificity (95% CI, 72.23–89.44% %) for the T brucei, T. congolense and T. vivax assays, respectively, under the conditions used. These findings indicate that the 7SL sRNA has many attributes that would be required for a potential diagnostic marker of AT: no cross-reaction with T. theileri, high specificity and sensitivity, early infection detection, continued signal even in the absence of detectable parasitaemia in blood, and clear discrimination between infected and treated animals.
Inequalities in Trust Levels and Compliance With Physical Distancing During COVID-19 Outbreaks: Comparing the Arab Minority and Jewish Populations in Israel
Authors: Shibli Haneen , Palkin Daiana , Aharonson-Daniel Limor , Davidovitch Nadav , Daoud Nihaya
Published: April 2022

Objectives: This study explores associations between trust in directives and compliance with physical distancing by comparing two populations in Israel.

Methods: Following two lockdowns, we conducted two cross-sectional surveys among the Arab minority and Jewish citizens of Israel (first survey, N = 613; second survey, N = 542). We conducted multivariable logistic regression analyses for the association between trust and compliance with physical distancing separately for each group in each survey.

Results: In both surveys trust levels were significantly lower among Arabs than Jews (p < 0.001). Compared to Jews, Arabs were less likely to report compliance with physical distancing in the first and second surveys (OR = 0.52, 95% CI 0.32–0.84 and OR = 0.62, 95% CI 0.39–0.98, respectively). In both surveys trusting the directives was an important determinant of compliance with physical distancing among Jews only.

Conclusion: Our findings indicate that momentum is important in building and maintaining public trust and compliance during pandemics. Policymakers should note the lack of trust among Arabs, which warrants further research and interventions.
Frequency of hypertension risk factors and level of knowledge among university students of twin cities in Pakistan
Authors:   Riphah College of Rehabilitation and Allied Health Sciences, Riphah International University Islamabad, Waseem Mehwish , Siddiqui Hafsa ,   Riphah College of Rehabilitation and Allied Health Sciences, Riphah International University Islamabad, Fazal Maham ,   Riphah College of Rehabilitation and Allied Health Sciences, Riphah International University Islamabad, Laiq Ifrah ,   Riphah College of Rehabilitation and Allied Health Sciences, Riphah International University Islamabad, Tariq Iqbal ,   Riphah College of Rehabilitation and Allied Health Sciences, Riphah International University Islamabad
Published: April 2022

Background: In Pakistan there is a high prevalence of hypertensive individuals. Identification of risk factors and their knowledge in young population could be advantageous. Objectives: To find the frequency of hypertension risk factors and level of knowledge among university students of twin cities within Pakistan. Methods: A cross sectional observational study was conducted among university students in twin cities of Pakistan. The sample size was 475. Male and female students with ages ranging from 18 to 30 years with no diagnosed cases of pulmonary and cardiac issues, cancer, physically disabled and impaired cognition were selected to fill the questionnaire. The WHO STEPS instrument was used to get the relevant information needed for this study which included demographics, tobacco use, diet, physical activity, and history of raised blood pressure, history of diabetes and also height and weight. Results: Out of 475 participants there were 235 (49%) males and 240 (51%) females. Knowledge score of 460 (96.8%) university students was poor. On the other hand, the frequency of risk factors was not found to be significant in this population. Conclusion: The study concluded that, although the frequency of risk factors for hypertension is low, university students of twin cities have poor knowledge regarding modifiable and non-modifiable risk factors of hypertension.
Patients satisfaction after primary total hip arthroplasty
Authors: Gul Hina , Awan Sadaf , Waqas Roohi , Butt Aymun , Fatima Zurriat , Kanwal Sobia
Published: April 2022

Background: Total hip arthroplasty is a surgery in which the diseased ball and socket of the hip joint is completely removed and replaced with artificial materials and satisfaction is a state felt by a person who has experienced a performance or an outcome that fulfill his or her expectation. Prevalence of total hip arthroplasty is 5.26%. Objectives: The objective of the study was to determine the patient satisfaction level after primary total hip arthroplasty. Methods: This was a descriptive cross sectional study with a sample size of 51 patients. Both genders are included with an age range of 45-65years and the patients who enrolled six months after surgery. Those patients were excluded who refused to participate in the study, those patients undergoing revision hip arthroplasty and patients who have any congenital deformity of lower limb. A self-administrated patient-satisfaction questionnaire was used. The questionnaire was valid and reliable and used in a previous study. Data was analyzed by using Statistical Package of Social Sciences (SPSS). Value of Cronbach's alpha was 0.86 which was considered highly reliable. Informed consent was obtained from every single patient. Results: Mean age of patients was 55.72, with range minimum 46 years to maximum 65 years. Satisfaction after six months of total hip arthroplasty in patients was somewhat high, 46.1% and the percentage of patients who were dissatisfied was 8.8%. Conclusion: Patient satisfaction is higher after total hip arthroplasty. Patients are satisfied with the result of the surgery, improving pain and improving functional activities.
Phenology, Morphology and Physiology Responses of Deficit Irrigated ‘Koroneiki’ Olive Trees as Affected by Environmental Conditions and Alternate Bearing
Authors: Siakou Melpomeni , Bruggeman Adriana , Eliades Marinos , Djuma Hakan , Kyriacou Marios C. , Moriana Alfonso
Published: April 2022

Climate change is affecting water resources in the Mediterranean region. In olive orchards, irrigation water use efficiency could be increased by accounting for trees’ alternate bearing behaviour and growth-stage sensitivity to drought. The main objective of this study is to examine olive tree phenology, morphology and physiology in “on” and “off” productive years for the improvement of irrigation scheduling. A regulated (RDI) and a sustained (SDI) deficit irrigation treatment were applied in a ‘Koroneiki’ olive orchard in Cyprus. Flowering occurred on 11 May 2019 and on 27 April 2021, which was caused by the lower temperatures in 2019. The Kc for the irrigation season, computed from daily water balance observations, was 0.37 in 2019 (38% canopy cover) and 0.41 in 2021 (62% canopy cover). Irrigation treatments did not significantly affect plant morphology and stem water potentials. In “on” years, shoot elongation ceased early in the season and stem water potential towards the end of September (−4.0 MPa) was lower than in the “off” year. Stem water potential recovery in the September of the “off” year indicated that irrigation could be less than 35% ETc in early fall. Water savings in RDI were 24–32% in “on” and 48% in “off” years relative to SDI, with no statistically significant effects on olive yields.
Genetic Diversity and Trends of Ancestral and New Inbreeding in Deutsch Drahthaar Assessed by Pedigree Data
Authors: Michels Paula Wiebke , Distl Ottmar
Published: April 2022

Loss of genetic diversity and high inbreeding rates confer an increased risk of congenital anomalies and diseases and thus impacting dog breeding. In this study, we analyzed recent and ancestral inbreeding as well as other measures of genetic variability in the Deutsch Drahthaar (DD) dog population. Analyses included pedigree data from 101,887 animals and a reference population with 65,927 dogs born between 2000 and 2020. The mean equivalent complete generations was 8.6 with 69% known ancestors in generation 8. The mean realized effective population size was 92 with an increasing trend from 83 to 108 over birth years. The numbers of founders, effective founders and effective ancestors, as well as founder genomes, were 814, 66, 38 and 16.15, respectively. Thirteen ancestors explained 50% of the genetic diversity. The mean coefficient of inbreeding and individual rate of inbreeding (ΔFi) were 0.042 and 0.00551, respectively, with a slightly decreasing trend in ΔFi. Exposure of ancestors to identical-by-descent alleles explored through ancestral coefficients of inbreeding showed a strong increasing trend. Comparisons between new and ancestral inbreeding coefficients according to Kalinowski et al. showed an average relative contribution of 62% of new inbreeding to individual inbreeding. Comparisons among average coancestry within the parental population and average inbreeding in the reference population were not indicative of genetic substructures. In conclusion, the creation of the DD dog breed about 120 years ago resulted in a popular breed with considerable genetic diversity without substructuring into lines or subpopulations. The trend of new inbreeding was declining, while ancestral inbreeding through ancestors who were autozygous at least once in previous generations was increasing.
Prolonged Endurance Exercise Adaptations Counteract Doxorubicin Chemotherapy-Induced Myotoxicity in Mice
Authors: Kwon Insu , Go Gwang-Woong , Lee Youngil , Kim Jong-Hee
Published: April 2022

Doxorubicin (DOX) is a potent chemotherapeutic agent widely used for various types of cancer; however, its accumulation causes myotoxicity and muscle atrophy. Endurance exercise (EXE) has emerged as a vaccine against DOX-induced myotoxicity. However, potential molecular mechanisms of EXE-mediated myocyte protection for the unfavorable muscle phenotype remain unelucidated. In addition, most studies have identified the short-term effects of DOX and EXE interventions, but studies on the prolonged EXE effects used as adjuvant therapy for chronic DOX treatment are lacking. Twelve-week-old adult male C57BL/6J mice were assigned to four groups: sedentary treated with saline (SED-SAL, n = 10), endurance exercise treated saline (EXE-SAL, n = 10), sedentary treated with doxorubicin (SED-DOX, n = 10), and endurance exercise treated with doxorubicin (EXE-DOX, n = 10). Mice were intraperitoneally injected with DOX (5 mg/kg) or saline five times biweekly for eight weeks, while a treadmill running exercise was performed. Body composition was assessed and then soleus muscle tissues were excised for histological and biochemical assays. Our data showed that DOX aggravated body composition, absolute soleus muscle mass, and distinct pathological features; also, TOP2B upregulation was linked to DOX-induced myotoxicity. We also demonstrated that EXE-DOX promoted mitochondrial biogenesis (e.g., citrate synthase). However, no alterations in satellite cell activation and myogenesis factors in response to DOX and EXE interventions were observed. Instead, SED-DOX promoted catabolic signaling cascades (AKT-FOXO3α-MuRF-1 axis), whereas EXE-DOX reversed its catabolic phenomenon. Moreover, EXE-DOX stimulated basal autophagy. We showed that the EXE-mediated catabolic paradigm shift is likely to rescue impaired muscle integrity. Thus, our study suggests that EXE can be recommended as an adjuvant therapy to ameliorate DOX-induced myotoxicity.
Droplet Digital PCR (ddPCR) Analysis for Detecting Shiga-Toxin-Producing Escherichia coli (STEC)
Authors: Mancusi Andrea , Fulgione Andrea , Girardi Santa , Di Maro Orlandina , Capuano Federico , Proroga Yolande T. R. , Cristiano Daniela
Published: April 2022

Verocytotoxin-producing Escherichia coli, also referred to as Shiga-toxin-producing Escherichia coli (STEC), can be transmitted to humans through person-to-person contact, consumption of contaminated food or water, or by direct contact with animals. Its clinical and economic consequences have prompted the development of alternative approaches to the official method of analysis “UNI CEN ISO/TS 13136: 2012”, which describes the identification of STEC through the detection of its main virulence genes. Recently, droplet digital PCR (ddPCR) has been proposed as a technique for the sequence-specific detection and direct quantification of nucleic acids. The present study aimed to investigate if ddPCR could be able to detect STEC in less time than that required by the official method. This study consisted of the ddPCR of slices of beef contaminated with STEC and of the sponges used for beef official control at the slaughter stage. The results showed the ability of ddPCR to detect STEC in slices of beef already after sample incubation for 7 h at 37 °C while, in the case of sponges used for official controls, 9 h at 37 °C was needed. In this way, the ddPCR could represent an efficient method for detecting STEC and providing results in less time than the official method.
Predicting Institution Outcomes for Inter Partes Review (IPR) Proceedings at the United States Patent Trial & Appeal Board by Deep Learning of Patent Owner Preliminary Response Briefs
Authors: Sokhansanj Bahrad A. , Rosen Gail L.
Published: April 2022

A key challenge for artificial intelligence in the legal field is to determine from the text of a party’s litigation brief whether, and why, it will succeed or fail. This paper shows a proof-of-concept test case from the United States: predicting outcomes of post-grant inter partes review (IPR) proceedings for invalidating patents. The objectives are to compare decision-tree and deep learning methods, validate interpretability methods, and demonstrate outcome prediction based on party briefs. Specifically, this study compares and validates two distinct approaches: (1) representing documents with term frequency inverse document frequency (TF-IDF), training XGBoost gradient-boosted decision-tree models, and using SHAP for interpretation. (2) Deep learning of document text in context, using convolutional neural networks (CNN) with attention, and comparing LIME and attention visualization for interpretability. The methods are validated on the task of automatically determining case outcomes from unstructured written decision opinions, and then used to predict trial institution or denial based on the patent owner’s preliminary response brief. The results show how interpretable deep learning architecture classifies successful/unsuccessful response briefs on temporally separated training and test sets. More accurate prediction remains challenging, likely due to the fact-specific, technical nature of patent cases and changes in applicable law and jurisprudence over time.
Determination of the Carbohydrate Profile and Invertase Activity of Adulterated Honeys after Bee Feeding
Authors: Kanelis Dimitrios , Liolios Vasilios , Tananaki Chrysoula , Rodopoulou Maria-Anna
Published: April 2022

The higher demand for honey from consumers, combined with its limited availability, has led to different types of honey adulteration, causing substantial economic as well as negative impacts on consumers’ nutrition and health. Therefore, a need has emerged for reliable and cost-effective quality control methods to detect honey adulteration to ensure both the safety and quality of honey. To simulate the process with those applied by beekeepers in real-time, bee colonies were fed with different types of bee feeding (sugar syrup, candy paste and commercial syrup). The produced samples were analyzed for their carbohydrate profile and their invertase activity with the aim to find the effects of bee feeding on the quality of the final product. Honey samples produced after feeding with commercial syrup presented low fructose (22.9 %) and glucose (31.7 %) concentrations and high content of maltose (20.1%), while the samples that came from bee feeding with sugar syrup and candy paste had high concentrations of sucrose (6.2 % and 3.2 %, respectively), exceeding in some cases the legislative limits. Moreover, the samples coming from sugar feeding had lower values of invertase activity, while the group with inverted syrup was clearly discriminated through multi-discriminant analysis. The invertase activity of control samples was found at 153.7 U/kg, which was significantly higher compared to the other groups. The results showed that bee feeding during honey production might lead to adulteration, which can be detected through routine analyses, including the carbohydrate profile and the invertase activity.
‘The Lucky Country’: How the COVID-19 Pandemic Revitalised Australia’s Lethargic Art Market
Authors: Archer Anita , Challis David M.
Published: April 2022

Since its publication in 1964, Australians have used the title of Donald Horne’s book, The Lucky Country, as a term of self-reflective endearment to express the social and economic benefits afforded to the population by the country’s wealth of geographical and environmental advantages. These same advantages, combined with strict border closures, have proven invaluable in protecting Australia from the ravages of the global COVID-19 pandemic, in comparison to many other countries. However, elements of Australia’s arts sector have not been so fortunate. The financial damage of pandemic-driven closures of exhibitions, art events, museums, and art businesses has been compounded by complex government stimulus packages that have excluded many contracted arts workers. Contrarily, a booming fine art auction market and commercial gallery sector driven by stay-at-home local collectors demonstrated remarkable resilience considering the extraordinary circumstances. Nonetheless, this resilience must be contextualised against a decade of underperformance in the Australian art market, fed by the negative impact of national taxation policies and a dearth of Federal government support for the visual arts sector. This paper examines the complex and contradictory landscape of the art market in Australia during the global pandemic, including the extension of pre-pandemic trends towards digitalisation and internationalisation. Drawing on qualitative and quantitative analysis, the paper concludes that Australia is indeed a ‘lucky country’, and that whilst lockdowns have driven stay-at-home collectors to kick-start the local art market, an overdue digital pivot also offers future opportunities in the aftermath of the pandemic for national and international growth.
NEX-GDDP Multimodel Ensemble vs. E-OBS—Evaluation of the Extreme Temperatures and Precipitation over Southeast Europe: Historical Comparison
Authors: Chervenkov Hristo , Slavov Kiril
Published: April 2022

The present study evaluates the National Aeronautics Space Administration (NASA) Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset that provides statistically downscaled CMIP5 historical and future climate projections of the daily precipitation sum and extreme temperatures at high spatial resolution. A multimodel ensemble from all 21 available models is composed and compared against gridded observations from E-OBS. The study is performed over Southeast Europe for the whole time span of the historical period of NEX-GDDP 1950–2005. The performance of the NEX-GDDP data was evaluated at multiple time scales such as annual, seasonal, monthly, and daily. The skill of the multimodel ensemble to reproduce the interannual variability, as well as the long-term trend, is also evaluated. Moreover, key climate indices of the Expert Team on Climate Change Detection and Indices (ETCCDI), derived from the ensemble extreme temperatures and precipitation are superimposed on their counterparts based on the reference dataset E-OBS. Findings of the performed research indicate that NEX-GDDP parameters are in good agreement with the reference over the considered period on monthly, seasonal and annual scales which agrees with the outcomes from similar studies for other parts of the world. There are also no systematic differences in the pattern of the biases of the minimum and maximum temperature. Generally, the multimodel ensemble reproduces the extreme temperatures significantly better than the precipitation sum. The analysis reveals also the nonnegligible inefficiency of the NEX-GDDP ensemble to reproduce the long-term trend of the considered parameters as well as the climate extremes expressed with the ETCCDI indices.
Machine-Learning Based Analysis of Liquid Water Path Adjustments to Aerosol Perturbations in Marine Boundary Layer Clouds Using Satellite Observations
Authors: Zipfel Lukas , Andersen Hendrik , Cermak Jan
Published: April 2022

Changes in marine boundary layer cloud (MBLC) radiative properties in response to aerosol perturbations are largely responsible for uncertainties in future climate predictions. In particular, the relationship between the cloud droplet number concentration (Nd, a proxy for aerosol) and the cloud liquid water path (LWP) remains challenging to quantify from observations. In this study, satellite observations from multiple polar-orbiting platforms for 2006–2011 are used in combination with atmospheric reanalysis data in a regional machine learning model to predict changes in LWP in MBLCs in the Southeast Atlantic. The impact of predictor variables on the model output is analysed using Shapley values as a technique of explainable machine learning. Within the machine learning model, precipitation fraction, cloud top height, and Nd are identified as important cloud state predictors for LWP, with dynamical proxies and sea surface temperature (SST) being the most important environmental predictors. A positive nonlinear relationship between LWP and Nd is found, with a weaker sensitivity at high cloud droplet concentrations. This relationship is found to be dependent on other predictors in the model: Nd–LWP sensitivity is higher in precipitating clouds and decreases with increasing SSTs.
Nanopower Integrated Gaussian Mixture Model Classifier for Epileptic Seizure Prediction
Authors: Alimisis Vassilis , Gennis Georgios , Touloupas Konstantinos , Dimas Christos , Uzunoglu Nikolaos , Sotiriadis Paul
Published: April 2022

This paper presents a new analog front-end classification system that serves as a wake-up engine for digital back-ends, targeting embedded devices for epileptic seizure prediction. Predicting epileptic seizures is of major importance for the patient’s quality of life as they can lead to paralyzation or even prove fatal. Existing solutions rely on power hungry embedded digital inference engines that typically consume several µW or even mW. To increase the embedded device’s autonomy, a new approach is presented combining an analog feature extractor with an analog Gaussian mixture model-based binary classifier. The proposed classification system provides an initial, power-efficient prediction with high sensitivity to switch on the digital engine for the accurate evaluation. The classifier’s circuit is chip-area efficient, operating with minimal power consumption (180 nW) at low supply voltage (0.6 V), allowing long-term continuous operation. Based on a real-world dataset, the proposed system achieves 100% sensitivity to guarantee that all seizures are predicted and good specificity (69%), resulting in significant power reduction of the digital engine and therefore the total system. The proposed classifier was designed and simulated in a TSMC 90 nm CMOS process, using the Cadence IC suite.
The Influence of Music Content Marketing on User Satisfaction and Intention to Use in the Metaverse: A Focus on the SPICE Model
Authors: Hwang RakGun , Lee MinKyung
Published: April 2022

The global market is experiencing stagnation and recession in the “untact era”, and the emergence of the metaverse provides platform support and presents a new paradigm. This study aims to provide a framework for content creators and marketers to verify the effectiveness of metaverse marketing. An analysis was carried out of the fit of the model and the hypotheses between the metaverse seamlessness, presence, interoperability, concurrence, and economic flow (SPICE) model factors, customer satisfaction, and purchase intention. In the test, 9 out of 11 hypotheses were accepted. In conclusion, the data are meaningful, and this study presents the value of music content marketing in the metaverse through the metaverse SPICE model.
Sulfur Vacancies Enriched 2D ZnIn2S4 Nanosheets for Improving Photoelectrochemical Performance
Authors: Hu Sujuan , Jin Li , Si Wangyu , Wang Baoling , Zhu Mingshan
Published: April 2022

Vacancies engineering based on semiconductors is an effective method to enhance photoelectrochemical activity. Herein, we used a facile one-step solvothermal method to prepare sulfur vacancies modified ultrathin two-dimensional (2D) ZnIn2S4 nanosheets. The photon-to-current efficiency of sulfur vacancies modified ultrathin 2D ZnIn2S4 nanosheets is 1.82-fold than ZnIn2S4 nanosheets without sulfur vacancies and 2.04-fold than multilayer ZnIn2S4. The better performances can be attributed to the introduced sulfur vacancies in ZnIn2S4, which influence the electronic structure of ZnIn2S4 to absorb more visible light and act as the electrons trapping sites to suppress the recombination of photo-generated carriers. These results provide a new route to designing efficient photocatalyst by introducing sulfur vacancies.
Thermocatalytic Hydrogenation of CO2 to Methanol Using Cu-ZnO Bimetallic Catalysts Supported on Metal–Organic Frameworks
Authors: Duma Zama G. , Dyosiba Xoliswa , Moma John , Langmi Henrietta W. , Louis Benoit , Parkhomenko Ksenia , Musyoka Nicholas M.
Published: April 2022

The thermocatalytic hydrogenation of carbon dioxide (CO2) to methanol is considered as a potential route for green hydrogen storage as well as a mean for utilizing captured CO2, owing to the many established applications of methanol. Copper–zinc bimetallic catalysts supported on a zirconium-based UiO-66 metal–organic framework (MOF) were prepared via slurry phase impregnation and benchmarked against the promoted, co-precipitated, conventional ternary CuO/ZnO/Al2O3 (CZA) catalyst for the thermocatalytic hydrogenation of CO2 to methanol. A decrease in crystallinity and specific surface area of the UiO-66 support was observed using X-ray diffraction and N2-sorption isotherms, whereas hydrogen-temperature-programmed reduction and X-ray photoelectron spectroscopy revealed the presence of copper active sites after impregnation and thermal activation. Other characterisation techniques such as scanning electron microscopy, transmission electron microscopy, and thermogravimetric analysis were employed to assess the physicochemical properties of the resulting catalysts. The UiO-66 (Zr) MOF-supported catalyst exhibited a good CO2 conversion of 27 and 16% selectivity towards methanol, whereas the magnesium-promoted CZA catalyst had a CO2 conversion of 31% and methanol selectivity of 24%. The prepared catalysts performed similarly to a CZA commercial catalyst which exhibited a CO2 conversion and methanol selectivity of 30 and 15%. The study demonstrates the prospective use of Cu-Zn bimetallic catalysts supported on MOFs for direct CO2 hydrogenation to produce green methanol.
Altered Spinal Homeostasis and Maladaptive Plasticity in GFAP Null Mice Following Peripheral Nerve Injury
Authors: De Luca Ciro , Virtuoso Assunta , Korai Sohaib Ali , Cirillo Raffaella , Gargano Francesca , Papa Michele , Cirillo Giovanni
Published: April 2022

The maladaptive response of the central nervous system (CNS) following nerve injury is primarily linked to the activation of glial cells (reactive gliosis) that produce an inflammatory reaction and a wide cellular morpho-structural and functional/metabolic remodeling. Glial acidic fibrillary protein (GFAP), a major protein constituent of astrocyte intermediate filaments (IFs), is the hallmark of the reactive astrocytes, has pleiotropic functions and is significantly upregulated in the spinal cord after nerve injury. Here, we investigated the specific role of GFAP in glial reaction and maladaptive spinal cord plasticity following sciatic nerve spared nerve injury (SNI) in GFAP KO and wild-type (WT) animals. We evaluated the neuropathic behavior (thermal hyperalgesia, allodynia) and the expression of glial (vimentin, Iba1) and glutamate/GABA system markers (GLAST, GLT1, EAAC1, vGLUT, vGAT, GAD) in lumbar spinal cord sections of KO/WT animals. SNI induced neuropathic behavior in both GFAP KO and WT mice, paralleled by intense microglial reaction (Iba1 expression more pronounced in KO mice), reactive astrocytosis (vimentin increase) and expression remodeling of glial/neuronal glutamate/GABA transporters. In conclusion, it is conceivable that the lack of GFAP could be detrimental to the CNS as it lacks a critical sensor for neuroinflammation and morpho-functional–metabolic rewiring after nerve injury. Understanding the maladaptive morpho-functional changes of glial cells could represent the first step for a new glial-based targeted approach for mechanisms of disease in the CNS.
An Unusual Case of Fatal Thoracoabdominal Gunshot Wound without Diaphragm Injury
Authors: Sablone Sara , Lagona Valeria , Introna Francesco
Published: April 2022

In case of thoracoabdominal gunshot wounds (GSW), diaphragmatic lesions are common autopsy findings. In these cases, the bullet’s path involves both the thorax and the abdomen, so the diaphragm (the muscle that separates the two cavities) is frequently damaged. In the present report we illustrate a very unusual autopsy finding, came up after a man was shot twice and affected by a lethal thoracoabdominal gunshot wound. In particular, as expected based on CT scans, the corpse exhibited a thoracic-abdominal path and a retained bullet in the abdomen, but no diaphragmatic lesions or hemorrhagic infiltrations of this muscle have been detected during the autopsy. After a scrupulous examination and the section of all the organs, the intracorporeal projectile’s path was reconstructed, inferring that the thoracoabdominal transit of the bullet extraordinarily had occurred in correspondence of the diaphragmatic inferior vena cava’s ostium, thus exploiting a natural passage without damaging the diaphragmatic muscle.
Metabolism and Vascular Retinopathies: Current Perspectives and Future Directions
Authors: Singh Charandeep
Published: April 2022

The retina is one of the most metabolically active organs in the body. Although it is an extension of the brain, the metabolic needs of the retina and metabolic exchanges between the different cell types in the retina are not the same as that of the brain. Retinal photoreceptors convert most of the glucose into lactate via aerobic glycolysis which takes place in their cytosol, yet there are immense numbers of mitochondria in photoreceptors. The present article is a focused review of the metabolic dysregulation seen in retinopathies with underlying vascular abnormalities with aberrant mitochondrial metabolism and Hypoxia-inducible factor (HIF) dependent pathogenesis. Special emphasis has been paid to metabolic exchanges between different cell types in retinopathy of prematurity (ROP), age-related macular degeneration (AMD), and diabetic retinopathy (DR). Metabolic similarities between these proliferative retinopathies have been discussed.
Combination Antiretroviral Therapy (cART) in Diabetes Exacerbates Diabetogenic Effects on Hippocampal Microstructure, Neurogenesis and Cytokine Perturbation in Male Sprague Dawley Rats
Authors: Asouzu Johnson Jaclyn , Ndou Robert , Mbajiorgu Ejikeme Felix
Published: April 2022

The increasing incidence of diabetes and HIV/AIDS–diabetes comorbidity in society has led to the prevalence of combination antiretroviral therapy (cART) in diabetes, with some reported neural effects. Therefore, the effects of cART and type two diabetes (T2D) on the hippocampal levels of cytokines, lipid peroxidation; histomorphology and neurogenesis were investigated. Adult male Sprague–Dawley rats were divided into four groups: DB (diabetic rats); DAV (diabetic rats treated with cART (efavirenz, emtricitabine and tenofovir); AV (normal rats treated with cART) and the NC group (with no treatment). Following ninety days of treatment, the rats were terminated, and the brains excised. Immunoassay (IL-1α, IL-6, TNFα and MDA); immunohistochemical (Ki67 and DCX) and cresyl violet histomorphology analyses were carried out on brain homogenates and sections, respectively. In comparison to the control, the results showed that cART significantly elevated the IL-6, TNFα and MDA levels, while DB and DAV significantly reduced the body weight, glucose tolerance, IL-1α, IL-6, TNFα and MDA levels. The hippocampal neuronal number was reduced in AV (dentate gyrus; DG region), in the DB group (Cornu Ammonis subregion 1; CA1 and DG regions only) and in DAV (all three hippocampal regions). Additionally, the expression of neurogenic markers Ki67 and doublecortin (DCX) were reduced in the diabetic group, with a greater reduction in the cART+T2D group compared to the control. Furthermore, the neuronal number at all hippocampal regions was negatively corelated with the diabetic parameters (FBG; fasting blood glucose, NFBG; non-fasting blood glucose, AUC; area under the glucose tolerance curve) but positively correlated with body weight. Additionally, the increase in the DG neuronal nuclei area of DB and DAV was significantly positively correlated with FBG, NFBG and AUC and inversely correlated with the estimated number of neurons and neurogenesis. These findings indicate that cART in diabetes (DAV) has similar effects as diabetes relative to the induction of oxidative stress and impairment of the cytokine immune response, but exacerbated neurotoxicity is observed in DAV, as shown by a significantly decreased DCX expression compared to DB and reduction in the number of Cornu Ammonis subregion 3 (CA3) hippocampal neurons, unlike in cART or the diabetes-alone groups.
Multipartite Correlations in Quantum Collision Models
Authors: Filippov Sergey
Published: April 2022

Quantum collision models have proved to be useful for a clear and concise description of many physical phenomena in the field of open quantum systems: thermalization, decoherence, homogenization, nonequilibrium steady state, entanglement generation, simulation of many-body dynamics, and quantum thermometry. A challenge in the standard collision model, where the system and many ancillas are all initially uncorrelated, is how to describe quantum correlations among ancillas induced by successive system-ancilla interactions. Another challenge is how to deal with initially correlated ancillas. Here we develop a tensor network formalism to address both challenges. We show that the induced correlations in the standard collision model are well captured by a matrix product state (a matrix product density operator) if the colliding particles are in pure (mixed) states. In the case of the initially correlated ancillas, we construct a general tensor diagram for the system dynamics and derive a memory-kernel master equation. Analyzing the perturbation series for the memory kernel, we go beyond the recent results concerning the leading role of two-point correlations and consider multipoint correlations (Waldenfelds cumulants) that become relevant in the higher-order stroboscopic limits. These results open an avenue for the further analysis of memory effects in collisional quantum dynamics.
Entropy Estimators in SAR Image Classification
Authors: Cassetti Julia , Delgadino Daiana , Rey Andrea , Frery Alejandro C.
Published: April 2022

Remotely sensed data are essential for understanding environmental dynamics, for their forecasting, and for early detection of disasters. Microwave remote sensing sensors complement the information provided by observations in the optical spectrum, with the advantage of being less sensitive to adverse atmospherical conditions and of carrying their own source of illumination. On the one hand, new generations and constellations of Synthetic Aperture Radar (SAR) sensors provide images with high spatial and temporal resolution and excellent coverage. On the other hand, SAR images suffer from speckle noise and need specific models and information extraction techniques. In this sense, the G0 family of distributions is a suitable model for SAR intensity data because it describes well areas with different degrees of texture. Information theory has gained a place in signal and image processing for parameter estimation and feature extraction. Entropy stands out as one of the most expressive features in this realm. We evaluate the performance of several parametric and non-parametric Shannon entropy estimators as input for supervised and unsupervised classification algorithms. We also propose a methodology for fine-tuning non-parametric entropy estimators. Finally, we apply these techniques to actual data.
Testability of Instrumental Variables in Linear Non-Gaussian Acyclic Causal Models
Authors: Xie Feng , He Yangbo , Geng Zhi , Chen Zhengming , Hou Ru , Zhang Kun
Published: April 2022

This paper investigates the problem of selecting instrumental variables relative to a target causal influence X→Y from observational data generated by linear non-Gaussian acyclic causal models in the presence of unmeasured confounders. We propose a necessary condition for detecting variables that cannot serve as instrumental variables. Unlike many existing conditions for continuous variables, i.e., that at least two or more valid instrumental variables are present in the system, our condition is designed with a single instrumental variable. We then characterize the graphical implications of our condition in linear non-Gaussian acyclic causal models. Given that the existing graphical criteria for the instrument validity are not directly testable given observational data, we further show whether and how such graphical criteria can be checked by exploiting our condition. Finally, we develop a method to select the set of candidate instrumental variables given observational data. Experimental results on both synthetic and real-world data show the effectiveness of the proposed method.
Adversarial Multiscale Feature Learning Framework for Overlapping Chromosome Segmentation
Authors: Mei Liye , Yu Yalan , Shen Hui , Weng Yueyun , Liu Yan , Wang Du , Liu Sheng , Zhou Fuling , Lei Cheng
Published: April 2022

Chromosome karyotype analysis is of great clinical importance in the diagnosis and treatment of diseases. Since manual analysis is highly time and effort consuming, computer-assisted automatic chromosome karyotype analysis based on images is routinely used to improve the efficiency and accuracy of the analysis. However, the strip-shaped chromosomes easily overlap each other when imaged, significantly affecting the accuracy of the subsequent analysis and hindering the development of chromosome analysis instruments. In this paper, we present an adversarial, multiscale feature learning framework to improve the accuracy and adaptability of overlapping chromosome segmentation. We first adopt the nested U-shaped network with dense skip connections as the generator to explore the optimal representation of the chromosome images by exploiting multiscale features. Then we use the conditional generative adversarial network (cGAN) to generate images similar to the original ones; the training stability of the network is enhanced by applying the least-square GAN objective. Finally, we replace the common cross-entropy loss with the advanced Lovász-Softmax loss to improve the model’s optimization and accelerate the model’s convergence. Comparing with the established algorithms, the performance of our framework is proven superior by using public datasets in eight evaluation criteria, showing its great potential in overlapping chromosome segmentation.
Entropy Analysis of the Thermal Convection of Nanosuspension within a Chamber with a Heat-Conducting Solid Fin
Authors: Le Xuan Hoang Khoa , Oztop Hakan F. , Selimefendigil Fatih , Sheremet Mikhail A.
Published: April 2022

Heat transport augmentation in closed chambers can be achieved using nanofluids and extended heat transfer surfaces. This research is devoted to the computational analysis of natural convection energy transport and entropy emission within a closed region, with isothermal vertical borders and a heat-conducting solid fin placed on the hot border. Horizontal walls were assumed to be adiabatic. Control relations written using non-primitive variables with experimentally based correlations for nanofluid properties were computed by the finite difference technique. The impacts of the fin size, fin position, and nanoadditive concentration on energy transfer performance and entropy production were studied. It was found that location of the long fin near the bottom wall allowed for the intensification of convective heat transfer within the chamber. Moreover, this position was characterized by high entropy generation. Therefore, the minimization of the entropy generation can define the optimal location of the heat-conducting fin using the obtained results. An addition of nanoparticles reduced the heat transfer strength and minimized the entropy generation.
Solar Technology and District Cooling System in a Hot Climate Regions: Optimal Configuration and Technology Selection
Authors: Ismaen Rabah , ElMekkawy Tarek Y. , Pokharel Shaligram , Elomri Adel , Al-Salem Mohammed
Published: April 2022

With the increasing need for cooling and the concerns for pollution due to fossil fuel-based energy use, renewable energy is considered an add-on to cooling technologies. The climatic condition in the Middle East, analyzed in this paper, provides the potential to integrate solar energy with the cooling system. Due to the availability of various solar energy and cooling technologies, multiple configurations of solar-cooling systems can be considered to satisfy the cooling demand. The research presented in this paper aims to assess and compare these configurations by considering the energy prices and the installation area. The proposed model is formulated in Mixed-Integer Linear Programming and optimizes the holistic system design and operation. The economic, renewable energy use, and environmental performances of the optimal solution for each configuration are analyzed and compared to the base grid-DCS configuration. Results show that the electricity tariff and the available installation area impact the economic competitiveness of the solar energy integration. When electricity tariff is subsided (low), the conventional grid-based DCS is the most competitive. The PV-DCS configuration is economically competitive among the solar assisted cooling systems, and it can contribute to reducing the environmental impact by 58.3%. The PVT-DCS configuration has the lowest operation cost and the highest environmental performance by decreasing the global warming potential by 89.5%. The T-DCS configuration becomes economically competitive only at high electricity tariffs.
Sliding Mode Observer for State-of-Charge Estimation Using Hysteresis-Based Li-Ion Battery Model
Authors: Chen Mengying , Han Fengling , Shi Long , Feng Yong , Xue Chen , Gao Weijie , Xu Jinzheng
Published: April 2022

Lithium-ion battery devices are essential for energy storage and supply in distributed energy generation systems. Robust battery management systems (BMSs) must guarantee that batteries work within a safe range and avoid the damage caused by overcharge and overdischarge. The state-of-charge (SoC) of Li-ion batteries is difficult to observe after batteries are manufactured. The hysteresis phenomenon influences the existing battery modeling and SoC estimation accuracy. This research applies a terminal sliding mode observer (TSMO) algorithm based on a hysteresis resistor-capacitor (RC) equivalent circuit model to enable accurate SoC estimation. The proposed method is evaluated using two dynamic battery tests: the dynamic street test (DST) and the federal urban driving schedule (FUDS) test. The simulation results show that the proposed method achieved high estimation accuracy and fast response speed. Additionally, real-time battery information, including battery output voltage and SoC, was acquired and displayed by an automatic monitoring system. The designed system is valuable for all battery application cases.
Permeability Modeling and Estimation of Hydrogen Loss through Polymer Sealing Liners in Underground Hydrogen Storage
Authors: Gajda Dawid , Lutyński Marcin
Published: April 2022

Fluctuations in renewable energy production, especially from solar and wind plants, can be solved by large-scale energy storage. One of the possibilities is storing energy in the form of hydrogen or methane–hydrogen blends. A viable alternative for storing hydrogen in salt caverns is Lined Rock Cavern (LRC) underground energy storage. One of the most significant challenges in LRC for hydrogen storage is sealing liners, which need to have satisfactory sealing and mechanical properties. An experimental study of hydrogen permeability of different kinds of polymers was conducted, followed by modeling of hydrogen permeability of these materials with different additives (graphite, halloysite and fly ash). Fillers in polymers can have an impact on the hydrogen permeability ratio and reduce the amount of polymer required to make a sealing liner in the reservoir. Results of this study show that hydrogen permeability coefficients of polymers and estimated hydrogen leakage through these materials are similar to the results of salt rock after the salt creep process. During 60 days of hydrogen storage in a tank of 1000 m2 inner surface, 1 cm thick sealing liner and gas pressure of 1.0 MPa, only approx. 1 m3 STP of hydrogen will diffuse from the reservoir. The study also carries out the modeling of the hydrogen permeability of materials, using the Maxwell model. The difference between experimental and model results is up to 17%, compared to the differences exceeding 30% in some other studies.