bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of osteoporosis medications on bone fracture in patients with chronic kidney disease
Authors: Kao Chih-Chin , Wu Pei-Chen , Chuang Ming-Tsang , Yeh Shu-Ching , Lin Yen-Chung , Chen Hsi-Hsien , Fang Te-Chao , Chang Wei-Chiao , Wu Mai-Szu , Chang Tzu-Hao
Published: January 2022

Purpose of the study

The risk of bone fracture is high in patients with chronic kidney disease (CKD), and aggressive treatment to reduce fragility fracture risk is the major strategy. However, the outcomes of osteoporosis medications in patients with CKD remain unclear.

Study design

Patients with stage 3–5 CKD during 2011–2019 were enrolled. Patients were divided into two groups based on receiving osteoporosis medications (bisphosphonates, raloxifene, teriparatide or denosumab) or not. Two groups were matched at a 1:1 ratio by using propensity scores. The outcomes of interest were bone fractures, cardiovascular (CV) events and all-cause mortality. Cox proportional hazard regression models were applied to identify the risk factors. Additional stratified analyses by cumulative dose, treatment length and menopause condition were performed.

Results and conclusions

67 650 patients were included. After propensity score matching, 1654 patients were included in the study and control group, respectively. The mean age was 70.2±12.4 years, and 32.0% of patients were men. After a mean follow-up of 3.9 years, the incidence rates of bone fracture, CV events and all-cause mortality were 2.0, 1.7 and 6.5 per 1000 person-months, respectively. Multivariate analysis results showed that osteoporosis medications reduced the risk of CV events (HR, 0.35; 95% CI, 0.18 to 0.71; p = 0.004), but did not alleviate the risks of bone fracture (HR, 1.48; 95% CI, 0.73 to 2.98; p = 0.28) and all-cause mortality (HR, 0.93; 95% CI, 0.67 to 1.28; p = 0.65). Stratified analysis showed that bisphosphonates users have most benefits in the reduction of CV events (HR, 0.26; 95% CI, 0.11 to 0.64; p = 0.003). In conclusion, osteoporosis medications did not reduce the risk of bone fractures, or mortality, but improved CV outcomes in patients with CKD.
Posterior reversible encephalopathy syndrome (PRES): diagnosis and management
Authors: Triplett James D , Kutlubaev Mansur Amirovich , Kermode Allan G , Hardy Todd
Published: January 2022

Posterior reversible encephalopathy syndrome (PRES) may present with diverse clinical symptoms including visual disturbance, headache, seizures and impaired consciousness. MRI shows oedema, usually involving the posterior subcortical regions. Triggering factors include hypertension, pre-eclampsia/eclampsia, renal failure, cytotoxic agents and autoimmune conditions. The mechanism underlying PRES is not certain, but endothelial dysfunction is implicated. Treatment is supportive and involves correcting the underlying cause and managing associated complications, such as seizures. Although most patients recover, PRES is not always reversible and may be associated with considerable morbidity and even mortality.
In vitro propagation ofVaccinium floribundumKunth from seeds: promissory technology for mortiño accelerated production
Authors: Meneses L.S. , Morillo L.E. , Vásquez-Castillo W.
Published: January 2022

The Andean mortiño (Vaccinium floribundum Kunth) grows wild in the northern paramos of South América. The berries present potential opportunities for agribusiness, but an efficient technology for the production of plants and berries is required. On the other hand, the development of plant production methods from mortiño seeds will allow the plants’ accessibility and its potential use in breeding programs. The objective of this study was to develop an efficient in vitro protocol for accelerated production using seeds. We carried out the research in four phases: seed germination, plant multiplication, rooting, and acclimatization in the greenhouse. For in vitro seed germination, we studied the effect of two culture media [woody plant medium (WPM) and Murashige and Skoog medium (MS], two photoperiods (16 and 24 hours of light), and two temperatures (18 and 28 °C). The best treatment was found to be WPM + 24 h light + 18 °C. In the micropropagation of seedlings, the effect of two concentrations of three cytokinines [(trans-zeatin riboside (TZR), zeatin (ZEA), and 2-isopentenyl adenine (2iP)], and two photoperiods (16 and 0 h light) was evaluated, whereby the concentration of 0.5 mg L−1of TZR was the best treatment. For rooting, two doses of three auxins [indole-3-butyric acid (IBA), 1-naphthaleneacetic acid (NAA), and indole-3-acetic acid (IAA)] were evaluated, resulting in the 2 mg·L−1concentration of IBA giving the best root induction. Finally, the in vitro rooted plants were acclimatized in a greenhouse. We found that peat was the best substrate. These results show that the technology developed here is useful for in vitro production of V. floribundum using seeds.
Role of gravitational decoupling on isotropization and complexity of self-gravitating system under complete geometric deformation approach
Authors: Maurya S. K. , Nag Riju
Published: January 2022

In the present paper, we discuss the role of gravitational decoupling to isotropize the anisotropic solution of Einstein’s field equations in the context of the complete geometric deformation (CGD) approach and its influence on the complexity factor introduced by Herrera (Phys Rev D 97:044010, 2018) in the static self-gravitating system. Moreover, we proposed a simple and effective technique as well to generate new solutions for self-gravitating objects via CGD approach by using two systems with the same complexity factor and vanishing complexity factor proposed by Casadio et al. (Eur Phys J C 79:826, 2019). The effect of decoupling constant and the compactness on the complexity factor have also been analyzed for the obtained solutions.
Gravitationally decoupled anisotropic solution using polytropic EoS in the framework of 5D Einstein–Gauss–Bonnet Gravity
Authors: Maurya S. K. , Govender M. , Singh Ksh. Newton , Nag Riju
Published: January 2022

In this work we explore the characteristics of a polytropic solution for the anisotropic stellar object within the framework of Einstein–Gauss–Bonnet (EGB) gravity. We introduce anisotropy via the minimally gravitational decoupling method. The analysis of the exact solution of the governing equation for the gravitational potentials reveals novel features of the compact object. We find that the EGB coupling constant and the decoupling parameter play important roles in enhancing and suppressing the effective density and radial profiles at each interior point of the bounded object. An analysis of the effective tangential pressure reveals a ‘changeover’ in the trends brought about by the EGB and decoupling constants which may be linked to the cracking observed in classical 4D stellar objects proposed by Herrera (Phys Lett A 165:206, 1992).
New Riccati equations for radiating matter
Authors: Naidoo Noeleen , Maharaj Sunil D. , Govinder Keshlan S.
Published: January 2022

The relationship between radiating stars in general relativity and Riccati equations is investigated for a general matter distribution including the electromagnetic field and the cosmological constant. A generalised transformation relating the gravitational potentials for a spherically symmetric relativistic gravitating fluid is introduced. This generates a new Riccati equation at the surface of the radiating star. Exact solutions to the boundary condition are found and the gravitational potentials are given explicitly. Some of the consistency conditions can be reduced to Bernoulli equations which admit exact solutions. We also demonstrate that the reduction of order allows us to write the boundary condition as a first order equation utilising the generalised transformation. Solutions obtained using the generalised transformation also admit a linear equation of state.
Repulsive Casimir force in stationary axisymmetric spacetimes
Authors: De La Hoz-Coronell V. , Gonçalves A. E. , Baldiotti M. C. , Batista R. C.
Published: January 2022

We study the influence of stationary axisymmetric spacetimes on Casimir energy. We consider a massive scalar field and analyze its dependence on the apparatus orientation with respect to the dragging direction associated with such spaces. We show that, for an apparatus orientation not considered before in the literature, the Casimir energy can change its sign, producing a repulsive force. As applications, we analyze two specific metrics: one associated with a linear motion of a cylinder and a circular equatorial motion around a gravitational source described by Kerr geometry.
Non-Gaussian effects of the Saha’s ionization in the early universe
Authors: Sales L. L. , Carvalho F. C. , Bento E. P. , Souza H. T. C. M.
Published: January 2022

Tsallis’ thermostatistical has received increasing attention due to its success in describing phenomena that manifest unusual thermodynamic properties. In this context, the generalized Saha equation must follow a condition of generalized thermal equilibrium of matter and radiation. The present work aims to explore the non-Gaussian effects on Saha’s ionization via Tsallis statistics. To accomplish this, we generalized the number density taking into account a non-Gaussian Fermi-Dirac distribution and then set out the Saha equation for the cosmological recombination. As a result, we highlight two new non-Gaussian effects: (i) two generalized chemical equilibrium conditions, one for the relativistic regime and the other for the non-relativistic one; and (ii) the hydrogen binding q-energy. We demonstrated that to yield smooth shifts in the binding energy, the a-parameter must be very small. We also showed that binding q-energy exhibits symmetrical behavior around the value of the standard binding energy. Besides, we used the q-energy in order to access other hydrogen energy levels, and we ascertained the values of the a-parameter that access those levels and their relationship to temperature. Finally, we employed these results to examine the non-Gaussian effects of the deuterium bottleneck, recombination, and the particle anti-particle excess.
Path integral analysis of the axial anomaly in Very Special Relativity
Authors: Bufalo R. , Ghasemkhani M.
Published: January 2022

In this note, we revise the problem of the axial anomaly in the framework of Very Special Relativity following Fujikawa’s path integral approach. We show nonperturbatively that no VSR contribution is present in the path integral measure in (3 + 1)-dimensional spacetime. Furthermore, we extend our results to (1 + 1) dimensions, as well as to the two-dimensional curved spacetime.
Magnetic field-assisted wakefield generation and electron acceleration by Gaussian and super-Gaussian laser pulses in plasma
Authors: Abedi-Varaki Mehdi , Kant Niti
Published: January 2022

This study focuses on electron acceleration and wakefield produced by Gaussian and Super-Gaussian (SG) laser pulses through plasma medium in the attendance of an external magnetic field. Two shapes of different laser spatial profiles Gaussian and SG are considered. Besides, governing equations for analysis of laser wakefield and electron acceleration by using of hydrodynamics fluid equations, Maxwell’s equations and perturbation technique for Gaussian and SG laser pulses in weakly nonlinear regime have been derived. In addition, influence of the external magnetic field strengths, laser intensity, the pulselength, the plasma electron density and the laser frequency on the wakefield and the electron energy gain have been investigated. Numerical results indicate that by increasing of external magnetic field, the amplitude of wakefield increases. Moreover, it is observed that wakefield amplitude excited by SG laser pulse in comparison with Gaussian laser pulse is larger when external magnetic field is increased. Furthermore, it is found that wakefield amplitude and shape of wakefield generation in within homogeneous plasma greatly are related to the laser profile type, selected laser parameters and external magnetic field. In addition, it is seen that influence of external magnetic field, while laser intensity enhances, on the electron energy gain in SG and Gaussian laser pulses is insignificant.
Hybrid Fuzzy AHP and Fuzzy TOPSIS Decision Model for Aquaculture Species Selection
Authors: Padma T. , Shantharajah S. P. , Ramadoss P.
Published: January 2022

Worldwide demand for fish products is increasing continuously. Literature evidence indicates that there is a persistent decrease in ocean fisheries’ supply. Aquaculture bridges the gap between the reduced ocean fish supply and increased world fish food demand. Sustainable and profitable aquaculture is firmly facilitated by selective fish species. Species selection has been achieved through deeply analyzing the manifold and complex interrelationships between the numerous subjective risk categories intricate in aquaculture. Apparently an analytical system able to analyze massive subjective stakes in terms of its quantifiable equivalent that aids selecting an optimal fish species is nontrivial. This research provides quantifiable metrics that eases the analytical struggle towards the subjective aspect of species selection. The novelty involves providing hybrid multi-criteria-based viable decision support methodology that analyses extensive aquaculture domain knowledge and inference and emulates the logic and reasoning process so as to choose an optimal fish species for aqua farming. The methodology is based on the assessment of several species in accordance with analyzing numerous associated criteria and sub-criteria of risk factors. This research consists of nineteen sub-criteria which were classified under five comprehensive heads of evaluation criteria such as environmental, nutritional, disease outbreaks, biotic and physiological risk categories. The weight scores for each criteria and sub-criteria were determined using the Fuzzy Analytical Hierarchy Processing (FAHP) method. Consequently using the derived priority weights, the best fish species to choose from several alternative species is identified based on the relative closeness values and ranks assigned to them by applying the fuzzy Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method. A case study is performed on five varieties of most favored fish species for consumption to exemplify the effectiveness of the proposed model. The sturdiness of the suggested model is validated against the two standing multiple criteria decision-making approaches such as fuzzy ordered weighted average and fuzzy extent analysis–fuzzy weighted average methods. The research outcome strongly aids aqua farmers to identify an optimal fish species.
Modeling for heterogeneous objects based on X language: A modeling method of algorithm-hardware
Authors: Liu Yue , Zhao Chun
Published: January 2022

With the development of system engineering and related technology, modeling and simulation of complex systems need to include many disciplines, modeling languages, simulation environments, etc. By using unified modeling language to build models, barriers among different fields can be broken; the efficiency of model integration can be improved. Generally, a complex system contains some integrated circuit modules, which can be used for control or calculation of the system. Compared with system model, integrated circuit model is more fine-grained and lower-level and contains logic for control and algorithms. Thus, a method that modeling integrated circuit by unified modeling language is necessary. In this paper, a unified modeling language is introduced, called X language, and a modeling method of algorithm-hardware based on the X language is proposed. First of all, the hardware characteristics of the Kalman filter algorithm are extracted by analyzing the algorithm. Second, X language models are built to describe the algorithm-hardware. Then, the X language models are converted to Very-High-Speed Integrated Circuit Hardware Description Language (VHDL). Finally, the algorithm-hardware models are simulated and verified. The results show that the algorithm-hardware modeling method based on X language is feasible.
Green Function Treatment of the Barocaloric Effect in Mn3GaN
Authors: Schilling Osvaldo F.
Published: January 2022

Following our previous work on the magnetocaloric compounds FeMnAsxP[Formula: see text], we obtain thermomagnetic properties for the barocaloric antiperovskite Mn3GaN, which has been investigated in recent years in view of its thermal response under pressure cycling. Its structure displays canting of spins and a volume dilation in the antiferromagnetic (AFM) transition, related to magnetoelastic coupling. A random-phase-approximation (RPA) Green function theoretical treatment is applied to a two-exchange parameter Heisenberg model, and the canting of the spins orientation in the (111) planes of the structure is considered in the model. The observed first-order AFM phase transitions are reproduced by the introduction of a biquadratic spin term in the Hamiltonian, coupled to the volume dilation in the transition. The model is able to predict a greater stability for the canted spin structure as compared with conventional AFM, if the magnitudes of Mn magnetic moments in these structures are taken from the literature. The calculations of quantities of interest for barocaloric applications reproduce quite well the available data on temperature changes and latent heat under pressure cycling, at adiabatic and isothermal conditions, respectively.
Outcomes of training in smart home technology adoption
Authors: Wright David , Shank Daniel B. , Yarbrough Thomas
Published: January 2022

While various forms of smart home technology have been available for decades, they have yet to achieve widespread adoption. Although they have risen in popularity during recent years, the general public continue to rate smart home devices as overly complex compared to their benefits. This article reports the results of an eight-month study into the effects of training on smart home technology adoption. Building upon the results of a previous study, and using the same living laboratory approach, we studied the effects of training on the attitudes of a group of residents toward use of smart home technology. Results show that training influences those attitudes toward smart home technology, including increased confidence in future use, and increased actual use of more complex smart home features. Results also indicate that users tended to seek out other users rather than training materials for advice, and that privacy concerns were not a deterrent to using smart home devices.
A Survey on Gaps between Mean-Variance Approach and Exponential Growth Rate Approach for Portfolio Optimization
Authors: Lai Zhao-Rong , Yang Haisheng
Published: January 2022

Portfolio optimization can be roughly categorized as the mean-variance approach and the exponential growth rate approach based on different theoretical foundations, trading logics, optimization objectives, and methodologies. The former and the latter are often used in long-term and short-term portfolio optimizations, respectively. Although the mean-variance approach could be applied to short-term portfolio optimization, the performance may not be satisfactory (same with the exponential growth rate approach to the long-term portfolio optimization). This survey mainly explores the gaps between these two approaches, and investigates what common ideas or mechanisms are beneficial. Besides, the evaluating framework of this field and some unsolved problems are also discussed.
Chinese EmoBank: Building Valence-Arousal Resources for Dimensional Sentiment Analysis
Authors: Lee Lung-Hao , Li Jian-Hong , Yu Liang-Chih
Published: January 2022

An increasing amount of research has recently focused on dimensional sentiment analysis that represents affective states as continuous numerical values on multiple dimensions, such as
valence-arousal (VA)
space. Compared to the categorical approach that represents affective states as distinct classes (e.g., positive and negative), the dimensional approach can provide more fine-grained (real-valued) sentiment analysis. However, dimensional sentiment resources with valence-arousal ratings are very rare, especially for the Chinese language. Therefore, this study aims to: (1) Build a Chinese valence-arousal resource called Chinese EmoBank, the first Chinese dimensional sentiment resource featuring various levels of text granularity including 5,512 single words, 2,998 multi-word phrases, 2,582 single sentences, and 2,969 multi-sentence texts. The valence-arousal ratings are annotated by crowdsourcing based on the
Self-Assessment Manikin (SAM)
rating scale. A corpus cleanup procedure is then performed to improve annotation quality by removing outlier ratings and improper texts. (2) Evaluate the proposed resource using different categories of classifiers such as lexicon-based, regression-based, and neural-network-based methods, and comparing their performance to a similar evaluation of an English dimensional sentiment resource.
Linguistically Driven Multi-Task Pre-Training for Low-Resource Neural Machine Translation
Authors: Mao Zhuoyuan , Chu Chenhui , Kurohashi Sadao
Published: January 2022

In the present study, we propose novel sequence-to-sequence pre-training objectives for low-resource machine translation (NMT):
Japanese-specific sequence to sequence (JASS)
for language pairs involving Japanese as the source or target language, and
English-specific sequence to sequence (ENSS)
for language pairs involving English. JASS focuses on masking and reordering Japanese linguistic units known as bunsetsu, whereas ENSS is proposed based on phrase structure masking and reordering tasks. Experiments on ASPEC Japanese–English & Japanese–Chinese, Wikipedia Japanese–Chinese, News English–Korean corpora demonstrate that JASS and ENSS outperform MASS and other existing language-agnostic pre-training methods by up to +2.9 BLEU points for the Japanese–English tasks, up to +7.0 BLEU points for the Japanese–Chinese tasks and up to +1.3 BLEU points for English–Korean tasks. Empirical analysis, which focuses on the relationship between individual parts in JASS and ENSS, reveals the complementary nature of the subtasks of JASS and ENSS. Adequacy evaluation using LASER, human evaluation, and case studies reveals that our proposed methods significantly outperform pre-training methods without injected linguistic knowledge and they have a larger positive impact on the adequacy as compared to the fluency.
Interactive Gated Decoder for Machine Reading Comprehension
Authors: Cui Yiming , Che Wanxiang , Yang Ziqing , Liu Ting , Qin Bing , Wang Shijin , Hu Guoping
Published: January 2022

Owing to the availability of various large-scale
Machine Reading Comprehension
(
MRC
) datasets, building an effective model to extract passage spans for question answering has been well studied in previous works. However, in reality, there are some questions that cannot be answered through the passage information, which brings more challenges to this task. In this article, we propose an
Interactive Gated Decoder
(
IG Decoder
), which focuses on modeling the interactions between the answer span prediction and no-answer prediction with a gating mechanism. We also propose a simple but effective approach for automatically generating pseudo training data, which aims to enrich the training data of the unanswerable questions. Experimental results on popular benchmark SQuAD 2.0 and NewsQA show that the proposed approaches yield consistent improvements over traditional BERT-large and strong ALBERT-xxlarge baseline systems. We also provide detailed ablations of the proposed method and error analysis on hard samples, which could be helpful in future research.
Arabic Word Sense Disambiguation for Information Retrieval
Authors: Abderrahim Mohammed Alaeddine , Abderrahim Mohammed El-Amine
Published: January 2022

In the context of using semantic resources for information retrieval, the relationship and distance between concepts are considered important for word sense disambiguation. In this article, we experiment with Conceptual Density and Random Walk with graph methods to enhance the performance of the Arabic Information Retrieval System. To do this, a medium-sized corpus was used. The results proved that Random Walk can enhance the performance of the information retrieval system by achieving a mean improvement of 13%, 16%, and 12% in terms of recall, precision, and F-score, respectively.
Technical debt resulting from architectural degradation and code smells
Authors: Das Dipta , Maruf Abdullah Al , Islam Rofiqul , Lambaria Noah , Kim Samuel , Abdelfattah Amr S. , Cerny Tomas , Frajtak Karel , Bures Miroslav , Tisnovsky Pavel
Published: January 2022

Poor design choices, bad coding practices, or the need to produce software quickly can stand behind technical debt. Unfortunately, manually identifying and managing technical debt gets more difficult as the software matures. Recent research offers various techniques to automate the process of detecting and managing technical debt to address these challenges. This manuscript presents a mapping study of the many aspects of technical debt that have been discovered in this field of study. This includes looking at the various forms of technical debt, as well as detection methods, the financial implications, and mitigation strategies. The findings and outcomes of this study are applicable to a wide range of software development life-cycle decisions.
Cognitive Aging and the Promise of Physical Activity
Authors: Erickson Kirk I. , Donofry Shannon D. , Sewell Kelsey R. , Brown Belinda M. , Stillman Chelsea M.
Published: January 2022

Is the field of cognitive aging irretrievably concerned with decline and deficits, or is it shifting to emphasize the hope of preservation and enhancement of cognitive function in late life? A fragment of an answer comes from research attempting to understand the reasons for individual variability in the extent and rate of cognitive decline. This body of work has created a sense of optimism based on evidence that there are some health behaviors that amplify cognitive performance or mitigate the rate of age-related cognitive decline. In this context, we discuss the role of physical activity on neurocognitive function in late adulthood and summarize how it can be conceptualized as a constructive approach both for the maintenance of cognitive function and as a therapeutic for enhancing or optimizing cognitive function in late life. In this way, physical activity research can be used to shape perceptions of cognitive aging.
Vibrational Spectroscopy of the Water Dimer at Jet-Cooled and Atmospheric Temperatures
Authors: Vogt Emil , Kjaergaard Henrik G.
Published: January 2022

The vibrational spectroscopy of the water dimer provides an understanding of basic hydrogen bonding in water clusters, and with about one water dimer for every 1,000 water molecules, it plays a critical role in atmospheric science. Here, we review how the experimental and theoretical progress of the past decades has improved our understanding of water dimer vibrational spectroscopy under both cold and warm conditions. We focus on the intramolecular OH-stretching transitions of the donor unit, because these are the ones mostly affected by dimer formation and because their assignment has proven a challenge. We review cold experimental results from early matrix isolation to recent mass-selected jet expansion techniques and, in parallel, the improvements in the theoretical anharmonic models. We discuss and illustrate changes in the vibrational spectra of complexes upon increasing temperature, and the difficulties in recording and calculating these spectra. In the atmosphere, water dimer spectra at ambient temperature are crucial.
Impact of Deposition Condition on the Morphology and Electrochemical Performance of Deposited F-Doped PbO2on Graphite Substrate in Primary PbO2-Zn Battery
Authors: Abedini Amin , Karkeabadi Reza
Published: January 2022

The impact of deposition process parameters (temperature, current density, Pb2+concentration, and time of deposition) on morphology, electrical resistance, and discharge performance of a graphite/PbO2cathode in a PbO2/zinc primary battery was investigated. The morphology, architecture, and phase composition of the PbO2deposits were studied by FESEM, EDX, and XRD. The AC impedance and discharge tests were utilized for the exploration of the interfacial process and discharge performance of PbO2deposits. The results indicate that the increment in temperature and decrease in current density leads to increased growth of PbO2deposits with mainlyβphase, formation of porous architecture, and a decrease in the charge transfer resistance (Rct). Also, with an increase in the deposition time to 30 min the Rctis increased due to the formation of PbO2deposit with more uniform and compact structure. The deposition from 0.1 mol l‒1Pb2+solutions results in the formation of flower-like grains, a more porous surface, and lower Rct. However, because of concentration polarization, the PbO2deposit prepared from 0.5 mol l‒1of Pb2+solutions, 55 °C temperature, 40 mA cm‒2current density, and 15 min deposition time shows the best discharge performance.
Crosslinked Polybenzimidazoles Containing Functional CrosslinkersAs High-Temperature Proton Exchange Membranes: Enhanced Strength and Conductivity
Authors: Meng Chao , Han Dongmei , Ren Shan , Wang Shuanjin , Xiao Min , Meng Yuezhong
Published: January 2022

In the present work, a cross-linked high-temperature proton exchange membrane based on poly [2, 2′-(p-oxydiphenylene)-5, 50-benzimidazole] (OPBI), imidazole (Im) and hexachlorocyclotriphosphazene (HCCP) was prepared and characterized, aiming at their future application in fuel cell devices. The composite membranes were characterized by Fourier transform infrared (FT-IR) spectroscopy, scanning electron microscope (SEM), energy dispersive X-ray (EDX) and thermogravimetric analysis (TGA). The results show that the PBI are successfully cross-linked by the cross-linking agent, and the membranes are uniform and compact, with excellent thermal stability. Phosphoric acid (PA) doped crosslinked membranes have excellent mechanical properties and proton conductivities. The tensile strength of PA-doped PBI-ImCCP-20% at room temperature is 20 MPa, and the proton conductivity reaches 53 mS cm−1 at 160 °C without humidification. H2/O2 fuel cell assembled with PA-doped PBI-ImCCP-20% membrane delivered a peak power density of 749 mW cm−2 at 160 °C under anhydrous conditions. The excellent performance of PBI-ImCCP series cross-linked membranes makes them potential candidate for HT-PEMFC applications.
Pennington Corner: On Its Own
Authors: Calvo Roque J.
Published: January 2022

It’s hard to believe we are celebrating five years of publishing Interface. It seems like only yesterday that we were putting the finishing touches on the first table of contents and Paul Kohl (the first editor of Interface) declared, “We have a magazine.” We certainly did have a magazine, and in December 1992, we published a 64-page, four-color, quarterly magazine that had a fresh point of view and an elegant new look. The five-year growth of Interface has been meteoric, and I am extremely proud of how the magazine has developed and how effectively it communicates Society information and ideals.
Organotypic Neurovascular Unit and Electrochemical Platform for Predictive Toxicology
Authors: Miller Dusty R. , McClain Ethan S. , Brown Jacquelyn A , May Jody C. , Wikswo John , McLean John A , Cliffel David E.
Published: January 2022

Organophosphates account for about a third (nine million kilograms in 2012) of all pesticides used in the U.S., yet are toxic to humans, with exposure leading to neurodegenerative disorders and death. The ability to identify organophosphate exposure and predict biological responses has been limited—with epidemiological studies being uncontrolled and murine studies being discordant—leaving critical questions unanswered. In my talk, I will present a platform that uses human-derived cells to form a model blood-brain barrier to perform controlled toxicological studies. As a proof-of-concept experiment, environmental exposure was simulated by adding chlorpyrifos (CPF), the most prevalent organophosphate used in the U.S., to the vascular side of this engineered blood-brain barrier unit. Then, chemical perturbations were probed using a combination of electrochemical assays and mass spectrometry. The substantial metabolic disruption induced by this commercial pesticide will be discussed as well as platform advances (microfluidics and sensors) that made the experiments possible. Broadly, this work may lead to early diagnosis of CPF exposure and inform policies around pesticide use.
Biological Properties of Aloysia gratissima (Gillies & Hook.) Tronc. (Verbenaceae)
Authors: Alijar Souza Maryelen , Petry Fernanda , Vidor Morgan Letícia , Dal Magro Jacir , Müller Liz G.
Published: January 2022

Aloysia gratissima is a plant native to America, with applications in folk medicine for a wide range of diseases, such as bronchial infections, lung disorders, nervous system disorders (depression, anxiety), and inflammatory processes, among others. However, investigations about this species and its biological actions are still scarce. This literature review was carried out using articles published in the past 30 years on the PubMed, SciELO, and Web of Science platforms, with the focus on the method of extraction, chemical composition, and clinical and preclinical studies on the pharmacological properties of A. gratissima. We noticed that the main constituents of A. gratissima are guaiol, pinocamphone, ß-pinene, and 1,8-cineole. Additionally, preclinical studies reveal that A. gratissima extracts present antidepressant, anti-inflammatory, antinociceptive, antibacterial, antifungal, and virucidal effects. The results also demonstrate that there is a greater interest on the part of researchers from 2012 onwards in studying A. gratissima extracts with potential for possible new drugs.
The Role of Maxillofacial Structure on Condylar Displacement in Maximum Intercuspation and Centric Relation
Authors: Radej Ilona , Szarmach Izabela
Published: January 2022

Purpose. This study is aimed at evaluating the impact of the craniofacial structure and occlusal conditions on the position of the articular heads of the mandibular condyles in the maximum intercuspal position (MIP) and comparing the centric relation (CR) and MIP of the mandibular condyles prior to orthodontic treatment. Methods. The studied group consisted of 33 women and 15 men (median age of 17.75 years). Contact points of opposing teeth in the MIP were assessed by hand‐held casts. Condylar displacement (CD) in three spatial planes on both sides was measured on models mounted in an articulator using a mandibular position indicator (MPI). Patients were divided into groups according to craniofacial structures (vertical and horizontal growth directions). The Mann‐Whitney, Kruskal‐Wallis, post hoc Dwass‐Steel‐Critchlow‐Fligner, and Pearson’s χ2 independence tests as well as Spearman’s nonparametric correlations were used in the statistical analyses. Results. Within the limitations of this study, no statistically significant correlation of CD with certain cephalometric measurements from a lateral cephalometric radiograph (ANB, SN‐ML, and SGo/NMe) was observed. Correlation, however, was found between condylar displacement in the transverse axis and the mandibular plane angle SN‐ML (p = 0.033) and also between condylar displacement in the anteroposterior axis and a midline shift of the mandible (p = 0.041). The results revealed a relationship between Angle’s classification of molar position on the right side and anteroposterior CD values (p = 0.006). Conclusions. Cephalometric measurements cannot be used to predict CD at the level of the condyles. Analysis of occlusal conditions of models mounted in an articulator is desirable for patients with Angle’s class I and lower jaw asymmetry.
An Optimal Credit Scoring Model Based on the Maximum Default Identification Ability for Chinese Small Business
Authors: Bai Xuepeng , Zhao Zhichong
Published: January 2022

The reasonable credit scoring model must have strong default identification ability, which means the credit scoring can effectively distinguish between defaulting and nondefaulting customers. The premise to determine the credit score of small enterprises is to determine the weight of indicators. This paper studies 3,045 Chinese small business loans, and two novel weighting methods “Wilks’ Lambda method” and “AUC value method” are proposed, The greater the weight they meet, the greater the ability of default identification. The five weighting methods of “Wilks’ lambda method,” “AUC value method,” “G1 method,” “entropy method,” and “mean square variance method” are compared. An important contribution of the paper is to discover that Wilks’ Lambda method is the most effective method for small business.
Identification of Novel Subtypes in Lung Adenocarcinoma: Evidence from Gene Set Variation Analysis in Tumor and Adjacent Nontumor Samples
Authors: Li Feng , Wan Bin , He Xuan , Li Xiaoqing
Published: January 2022

In patients with lung adenocarcinoma (LUAD), the prognostic role of adjacent nontumor tissues is still unknown. Alterations in the activity of immunologic and hallmark gene sets in adjacent nontumor tissues may have a potential influence on cell proliferation of normal lung cell after pulmonary lobectomy. We sought to discover LUAD subgroups and prognostic gene sets based on changes in gene set activity in tumor and adjacent nontumor tissues. Firstly, we used gene set variation analysis (GSVA) to characterize the activity changes of 4922 gene sets in LUAD and nontumor samples. Luckily, we identified three novel LUAD subtypes using the nonnegative matrix factorization (NMF) algorithm. In detailed, patients with subtype-3 had a favorable prognosis, but subtypes 1 and 2 had a bad prognosis. In addition, patients with subtype-3 in the validation cohort also lived longer. Meanwhile, using the LASSO-Cox algorithm, we discovered 15 prognostic gene sets in tumors (T gene sets) and two prognostic gene sets in adjacent nontumors (N gene sets). Interestingly, genes from N gene sets were related with immune response in nontumor tissues, but genes from T gene sets were correlated with DNA damaging and repairing in tumor tissues. These findings highlighted the possibility of a stronger immune response in nearby nontumor tissues. In conclusion, our study established a theoretical foundation for selecting therapy strategy for LUAD patients that should be guided by changes in activity in tumor and adjacent nontumor tissues, particularly after pulmonary lobectomy.
A New Approach to Model Machine Learning by Using Complex Bipolar Intuitionistic Fuzzy Information
Authors: Jan Naeem , Maqsood Rabia , Nasir Abdul , Alhilal Mohsin S. , Alabrah Amerah , Al-Aidroos Naziha
Published: January 2022

Many industries are developing robust models, capable of analyzing huge and complex data by using machine learning (ML) while delivering faster and more accurate results on vast scales. ML is a subfield of artificial intelligence, which is broadly defined as the capability of a machine to imitate intelligent human behavior. ML tools enable organizations to swiftly identify profitable opportunities and potential risks. Besides these uses, ML also has a wide range of applications in our daily lives. So, the development in ML is most important in this age of digital system to solve more complex problems. In order to further develop ML and diminish the uncertainties to improve accuracy, an innovative concept of complex bipolar intuitionistic fuzzy sets (CBIFSs) is introduced in this article. Further, the Cartesian product of two CBIFSs is defined. Moreover, the complex bipolar intuitionistic fuzzy relations (CBIFRs) and their types with suitable examples are defined. In addition, some important results and properties are also presented. The proposed modeling techniques are used to study different ML factors and their interrelationship, so that the functionality of ML might be enhanced. Furthermore, the advantages and benefits of proposed methods are described by their side to side comparison with preexisting frameworks in the literature.
Identification of Biomarkers Associated with Cancerous Change in Oral Leukoplakia Based on Integrated Transcriptome Analysis
Authors: Li Chunshen , Shi Yingying , Zuo Lihua , Xin Mingzhe , Guo Xiaomeng , Sun Jianli , Chen Shuai , Zhao Bin , Yang Zhe , Sun Zhi , Zhao Hongyu
Published: January 2022

Objective. Oral leukoplakia (OLK) is the most common precancerous lesion in the oral cavity. This study aimed to explore key biomarkers for monitoring OLK for early diagnosis of oral squamous cell carcinoma (OSCC) and screen small-molecule drugs for the prevention of OSCC. Method. The Gene Expression Omnibus (GEO) database was explored to extract two microarray datasets, namely, GSE85195 and GSE25099. The data of the normal group, OLK group, and OSCC group were analyzed by weighted gene coexpression network analysis (WGCNA) to identify the most significant gene module and differentially expressed genes (DEGs). The intersection genes were extracted as the key genes of OLK carcinogenesis. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed in the module. Connectivity Map and molecular docking were used to screen small-molecule drugs. The diagnostic values of four key genes were identified and verified in the GSE26549 dataset. Results. WGCNA obtained the red module (r = −0.91,

p
<
0.05

) with the strongest correlation with cancerous phenotype. GO enrichment analysis showed 60 pathways, including 28 biological processes, 11 cell components, and 21 molecular functions, and KEGG enrichment analysis showed 4 pathways (

p
<
0.05

). In the differential expression analysis, there was no intersection between the upregulated genes and the red module genes. However, the intersection of the downregulated genes and the red module genes yielded 4 key genes: dopachrome tautomerase (DCT), keratin 3 (KRT3), keratin 76 (KRT76), and FAM3 metabolic regulation signal molecule B (FAM3B). The area under the curve of the diagnostic model constructed by these four genes was 0.963 (CI = 0.913–1.000). The sensitivity was 0.933, and the specificity was 0.923. The diagnostic model was successfully verified in GSE26549 (AUC = 0.745, CI = 0.638–0.851). Compared with the diagnostic models of the previous studies, the diagnostic efficiency of this model was the highest. The small-molecule drugs, selumetinib and benidipine, were selected according to the gene expression profile and showed binding activity when docking with the above molecules. Conclusions. This study provides new targets and drugs for OLK. These targets could be used as the key diagnostic molecules for long-term follow-up of OLK. The small-molecule drugs selumetinib and benidipine could be used for the prevention and treatment of OSCC.
Proactive Hedging European Option Pricing with a General Logarithmic Position Strategy
Authors: Qiao Lixin , Sun Fangfang , Qiao Xiaotuo , Li Meng , Wang Xuefeng
Published: January 2022

This study proposes an exotic option that extends the classical European option by requiring option holders to continuously trade in underlying assets according to a predesignated trading strategy with a general logarithmic position. The pricing formula for the exotic option with a general logarithmic strategy is derived from the Black–Scholes option pricing formula, and its price advantage is compared (based on simulations) to the classical European option and to the exotic option with a linear position. By varying key parameters, we found that the exotic option with a general logarithmic position has a significant price advantage (up to 34% under certain parameter settings) over the classical European option. Moreover, the exotic option with a general logarithmic strategy can save 5.5% more of the option premium than applying a linear position strategy. Our simulation results indicate that the price advantage of this proactive hedging option with a general logarithmic strategy depends heavily on the initial amount of capital; in particular, this exotic option is more suitable for traders with limited initial amounts of capital.
Endoatmospheric Ascent Optimal Guidance with Analytical Nonlinear Trajectory Prediction
Authors: Zhao Shilei , Chen Wanchun , Yang Liang
Published: January 2022

In this paper, an endoatmospheric ascent optimal guidance law with terminal constraint is proposed, which is under the framework of predictor-corrector algorithm. Firstly, a precise analytical nonlinear trajectory prediction with arbitrary Angle of Attack (AOA) profile is derived. This derivation process is divided into two steps. The first step is to derive the analytical trajectory with zero AOA using a regular perturbation method. The other step is to employ pseudospectral collocation scheme and regular perturbation method to solve the increment equation so as to derive the analytical solution with arbitrary AOA profile. The increment equation is formulated by Taylor expansion around the trajectory with zero AOA which remains the second order increment terms. Therefore, the resulting analytical solutions are the nonlinear functions of high order terms of arbitrary AOA values discretized in Chebyshev-Gauss-Legendre points, which has high accuracy. Secondly, an iterative correction scheme using analytical gradient is proposed to solve the endoatmospheric ascent optimal guidance problem, in which the dynamical constraint is enforced by the resulting analytical solutions. It only takes a fraction of a second to get the guidance command. Nominal simulations, Monte Carlo simulations, and optimality verification are carried out to test the performance of the proposed guidance law. The results show that it not only performs well in providing the optimal guidance command, but also has great applicability, high guidance accuracy and computational efficiency. Moreover, it has great robustness even in large dispersions and uncertainties.
Role of Salivary Biomarkers in Cystic Fibrosis: A Systematic Review
Authors: Almeslet Asma , Alnamlah Sarah , Alanzan Latifa , Aldriwesh Rawan , AlWehaiby Sha’eah
Published: January 2022

Background. Saliva biomarkers could be easily used as a noninvasive alternative tool for diagnosing cystic fibrosis (CF) disease. In this study, the significance of changes in salivary compositions in patients with CF was systematically reviewed. Methods. An electronic search was utilized to include studies published in English, with case‐control, cohort, or cross‐sectional design. The evaluated salivary components were extracted and summarized. The included studies were assessed using the Strengthening the Reporting of Observational Studies in Epidemiology checklist. Results. Out of 498 identified studies, nine met the eligibility criteria. Salivary electrolytes showed a substantial alteration in the CF group, especially with chloride and sodium. Total protein concentration was higher in patients with CF. However, SCN– concentration was lower in patients with CF. In addition, a reduction in the salivary flow rate and amylase levels was found in patients with CF. Conclusion. Alterations in salivary biomarkers among patients with CF could be used as a promising diagnostic tool for cystic fibrosis.