bluuebunny/crossref_metadata_2025 huggingface dataset:
A Multi-Center Study of CT-Based Neck Nodal Radiomics for Predicting an Adaptive Radiotherapy Trigger of Ill-Fitted Thermoplastic Masks in Patients with Nasopharyngeal Carcinoma
Authors: Lam Sai-Kit , Zhang Jiang , Zhang Yuan-Peng , Li Bing , Ni Rui-Yan , Zhou Ta , Peng Tao , Cheung Andy Lai-Yin , Chau Tin-Ching , Lee Francis Kar-Ho , Yip Celia Wai-Yi , Au Kwok-Hung , Lee Victor Ho-Fun , Chang Amy Tien-Yee , Chan Lawrence Wing-Chi , Cai Jing
Published: February 2022

Significant lymph node shrinkage is common in patients with nasopharyngeal carcinoma (NPC) throughout radiotherapy (RT) treatment, causing ill-fitted thermoplastic masks (IfTMs). To deal with this, an ad hoc adaptive radiotherapy (ART) may be required to ensure accurate and safe radiation delivery and to maintain treatment efficacy. Presently, the entire procedure for evaluating an eligible ART candidate is time-consuming, resource-demanding, and highly inefficient. In the artificial intelligence paradigm, the pre-treatment identification of NPC patients at risk for IfTMs has become greatly demanding for achieving efficient ART eligibility screening, while no relevant studies have been reported. Hence, we aimed to investigate the capability of computed tomography (CT)-based neck nodal radiomics for predicting IfTM-triggered ART events in NPC patients via a multi-center setting. Contrast-enhanced CT and the clinical data of 124 and 58 NPC patients from Queen Elizabeth Hospital (QEH) and Queen Mary Hospital (QMH), respectively, were retrospectively analyzed. Radiomic (R), clinical (C), and combined (RC) models were developed using the ridge algorithm in the QEH cohort and evaluated in the QMH cohort using the median area under the receiver operating characteristics curve (AUC). Delong’s test was employed for model comparison. Model performance was further assessed on 1000 replicates in both cohorts separately via bootstrapping. The R model yielded the highest “corrected” AUC of 0.784 (BCa 95%CI: 0.673–0.859) and 0.723 (BCa 95%CI: 0.534–0.859) in the QEH and QMH cohort following bootstrapping, respectively. Delong’s test indicated that the R model performed significantly better than the C model in the QMH cohort (p < 0.0001), while demonstrating no significant difference compared to the RC model (p = 0.5773). To conclude, CT-based neck nodal radiomics was capable of predicting IfTM-triggered ART events in NPC patients in this multi-center study, outperforming the traditional clinical model. The findings of this study provide valuable insights for future study into developing an effective screening strategy for ART eligibility in NPC patients in the long run, ultimately alleviating the workload of clinical practitioners, streamlining ART procedural efficiency in clinics, and achieving personalized RT for NPC patients in the future.
Preliminary In Vitro Cytotoxicity, Mutagenicity and Antitumoral Activity Evaluation of Graphene Flake and Aqueous Graphene Paste
Authors: Lamponi Stefania
Published: February 2022

This study aimed to determine the in vitro cytotoxicity and mutagenicity of graphene flake (GF) and aqueous graphene paste (AGP) in order to evaluate their potential for application as biomaterials. Furthermore, their antitumor activity against adherent and suspended cells, namely, human breast adenocarcinoma cells (MDA-MB-231), and human monocytes from histiocytic lymphoma (U-937), was investigated. The results demonstrated that GF reduced the viability and proliferation of NIH3T3 immortalized murine fibroblasts for concentrations >0.8 µg/mL and incubation times of 48 and 72 h. AGP showed no toxic effects in any of the tested concentrations and incubation times. The same results were obtained for MDA-MB-231 cells. The viability of the U-937 cells was not affected by either GF or AGP. The Ames test showed that GF and AGP were not genotoxic against Salmonella typhimurium strains TA98 and TA100, with and without metabolic activation. The present study demonstrated good in vitro cellular compatibility of GF and AGP and. Among these, AGP was the best material as it did not interfere, at any of the tested concentrations, with cell viability and proliferation for up to 72 h of incubation. In any case, neither material induced alterations to cell morphology and were not mutagenic.
Blue Light-Induced Retinal Neuronal Injury and Amelioration by Commercially Available Blue Light-Blocking Lenses
Authors: Theruveethi Nagarajan , Bui Bang Viet , Joshi Manjunath B. , Valiathan Manna , Ganeshrao Shonraj Ballae , Gopalakrishnan Sivakumar , Kabekkodu Shama Prasada , Bhat Shailaja S. , Surendran Sudarshan
Published: February 2022

Blue light exposure-induced retinal damage has been extensively studied. Although many in vitro studies have shown the benefits of blue light-blocking lenses (BBL) there have been few comprehensive in vivo studies to assess the effects of BBL. We investigated the influence of blue light exposure using light-emitting diodes on retinal histology and visual cortex neurons in rodents. We also considered whether retinal and cortical changes induced by blue light could be ameliorated with blue light-blocking lenses. A total of n = 24 (n = 6 in each group; control, light exposure without lenses, two different BBLs)) male Wistar rats were subjected to blue light exposure (LEDs, 450–500 lux) without or with BBLs (400–490 nm) for 28 days on a 12:12 h light–dark cycle. Histological analysis of retinae revealed apoptosis and necrosis of the retinal pigment epithelium (RPE), photoreceptors, and inner retina in the light exposure (LE) group, along with increase caspase-3 immunostaining in the ganglion cell layer (p < 0.001). BBL groups showed less caspase-3 immunostaining compared with the LE group (p < 0.001). V1-L5PNs (primary visual cortex layer 5 pyramidal neurons) demonstrated reduced branching and intersections points for apical (p < 0.001) and basal (p < 0.05) dendrites following blue light exposure. Blue light-blocking lenses significantly improved the number of basal branching points compared with the LE group. Our study shows that prolonged exposure to high levels of blue light pose a significant hazard to the visual system resulting in damage to the retina with the associated remodeling of visual cortex neurons. BBL may offer moderate protection against exposure to high levels of blue light.
Finite Element Modeling on Shear Performance of Grouted Stud Connectors for Steel–Timber Composite Beams
Authors: Zhang Henan , Ling Zhibin
Published: February 2022

Steel–timber composite (STC) systems are considered as an environmentally friendly alternative to steel–concrete composite (SCC) structures due to its advantages including high strength-to-weight ratio, lower carbon footprint, and fully dry construction. Bolts and screws are the most commonly used connectors in STC system; however, they probably make great demands on the accuracy of construction because of the predrilling in both the timber slabs and steel girder fangles. To address this issue, the STC connections with grouted stud connectors (GSC) were proposed in this paper. In addition, stud connectors can also provide outstanding stiffness and load-bearing capacity. The mechanical characteristic of the GSC connections was exploratorily investigated by finite element (FE) modeling. The designed parameters for the FE models include stud diameter, stud strength, angle of outer layer of cross-laminated timber (CLT) panel, tapered groove configurations, and thickness of CLT panel. The numerical results indicated that the shear capacity and stiffness of the GSC connections were mainly influenced by stud diameter, stud strength, angle of outer layer of CLT panel, and the angle of the tapered grooves. Moreover, the FE simulated shear capacity of the GSC connections were compared with the results predicted by the available calculation formulas in design codes and literatures. Finally, the group effect of the GSC connections with multiple rows of studs was discussed based on the numerical results and parametric analyses. An effective row number of studs was proposed to characterize the group effect of the GSC connections.
On-Demand Hydrogen Generation by the Hydrolysis of Ball-Milled Aluminum–Bismuth–Zinc Composites
Authors: Davies Jamey , du Preez Stephanus P. , Bessarabov Dmitri G.
Published: February 2022

In this investigation, ternary Al-Bi-Zn composites were prepared through mechanochemical activation to determine the combined effects of low-cost Bi and Zn on the morphology change and reactivity of the Al composite during the hydrolysis reaction. Specifically, Zn was considered as a means to slow the hydrogen generation rate while preserving a high hydrogen yield. A steady hydrogen generation rate is preferred when coupled with a proton exchange membrane fuel cell (PEMFC). Scanning electron microscopy (SEM) analysis indicated that Bi and Zn were distributed relatively uniformly in Al particles. By doing so, galvanic coupling between anodic Al and the cathodic Bi/Zn sustains the hydrolysis reaction until the entire Al particle is consumed. X-ray diffraction analysis (XRD) showed no intermetallic phases between Al, Bi, and/or Zn formed. A composite containing 7.5 wt% Bi and 2.5 wt% Zn had a hydrogen yield of 99.5%, which was completed after approximately 2300 s. It was further found that the water quality used during hydrolysis could further slow the hydrogen generation rate.
Statistical Simulation of the Switching Mechanism in ZnO-Based RRAM Devices
Authors: Bature Usman Isyaku , Nawi Illani Mohd , Khir Mohd Haris Md , Zahoor Furqan , Algamili Abdullah Saleh , Hashwan Saeed S. Ba , Zakariya Mohd Azman
Published: February 2022

Resistive random access memory (RRAM) has two distinct processes, the SET and RESET processes, that control the formation and dissolution of conductive filament, respectively. The laws of thermodynamics state that these processes correspond to the lowest possible level of free energy. In an RRAM device, a high operating voltage causes device degradation, such as bends, cracks, or bubble-like patterns. In this work, we developed a statistical simulation of the switching mechanism in a ZnO-based RRAM. The model used field-driven ion migration and temperature effects to design a ZnO-based RRAM dynamic SET and RESET resistance transition process. We observed that heat transport within the conducting filament generated a great deal of heat energy due to the carrier transport of the constituent dielectric material. The model was implemented using the built-in COMSOL Multiphysics software to address heat transfer, electrostatic, and yield RRAM energy. The heat energy increased with the increase in the operating power. Hence, the reliability of a device with high power consumption cannot be assured. We obtained various carrier heat analyses in 2D images and concluded that developing RRAM devices with low operating currents through material and structure optimization is crucial.
Recent Advances on Thermoelectric Silicon for Low-Temperature Applications
Authors: Narducci Dario , Giulio Federico
Published: February 2022

Silicon is the most widely used functional material, as it is geo-abundant and atoxic. Unfortunately, its efficiency as a thermoelectric material is very poor. In this paper, we present and discuss advances of research on silicon and related materials for thermoelectric applications, mostly focusing on the comparison between the two strategies deployed to increase its performance, namely either reducing its thermal conductivity or, in polycrystalline materials, increasing its power factor. Special attention will be paid to recent results concerning silicon thin films. The enhancement of Si performances has motivated efforts to develop integrated heat microharvesters operating around room temperature, which will be reviewed also in view of their applications to power wireless sensors for the Internet of Things.
Microstructural Evolution and Tensile Properties of Al0.3CoCrFeNi High-Entropy Alloy Associated with B2 Precipitates
Authors: Wang Xiaodi , Zhang Zhe , Wang Zhengbin , Ren Xuechong
Published: February 2022

The room-temperature strength of Al0.3CoCrFeNi high-entropy alloys (HEAs) is relatively low owing to its intrinsic fcc structure. In the present study, the as-cast HEAs were subjected to cold rolling and subsequent annealing treatment (800, 900, and 1000 °C) to adjust the microstructures and tensile properties. This treatment process resulted in the partial recrystallization, full recrystallization, and grain coarsening with increasing the annealing temperature. It was found that the large and spherical B2 precipitates were generated in the recrystallized grain boundaries of three annealing states, while the small and elongated B2 precipitates were aligned along the deformation twins in the non-recrystallized region of the 800 °C-annealing state. The former B2 precipitates assisted in refining the recrystallized grains to quasi ultra-fine grain and fine grain regimes (with the grain sizes of ~0.9, ~2.2, and ~7.2 μm). The tensile results indicated that the decreased annealing temperature induced the gradual strengthening of this alloy but also maintained the ductility at the high levels. The yield strength and ultimate tensile strength in 800 °C-annealed specimen were raised as high as ~870 and ~1060 MPa and the ductility was maintained at ~26%. The strengthening behavior derived from the heterogeneous microstructures consisting of quasi ultra-fine recrystallized grains, non-recrystallized grains, deformation twins, dislocations, and B2 precipitates. Current findings offer the guidance for designing the HEAs with good strength and ductility.
Permeability of Magnetic Cores with Air Gaps
Authors: Starodubtsev Yuri N. , Tsepelev Vladimir S. , Belozerov Vladimir Ya. , Zelenin Viktor A.
Published: February 2022

The influence of the geometric dimensions of the cut core and the number and size of air gaps on the effective permeability was investigated. Using dimensional analysis, an equation was obtained that relates the permeability of the cut core to the simplest dimensionless combination of the mean magnetic flux length l, single air gap length lg1, the cross-sectional area S of the core, and gap number ng. Permeability calculated from the geometric parameters of the cut core was compared with the effective permeability obtained using a two-dimensional FEMM simulation. Simulation has shown that the equation derived from dimensional analysis provides the best fit. The influence of each significant parameters l, lg1, ng, and S on cut core permeability is demonstrated. Experimental results have shown that an equation derived from dimensional analysis can be used to predict cut core permeability. In this case, one should take into account the residual air gap that forms after cutting the core. A method for assessing the residual air gap is proposed.
Reaction Kinetics and Process Model of the Polyacrylonitrile Fibers Stabilization Process Based on Dielectric Measurements
Authors: Hofele Julia , Link Guido , Jelonnek John
Published: February 2022

Microwave-based dielectric heating is a suitable method for energy- and time-efficient processes. Considering the energy required in the production of carbon fibers, it is evident that microwave-based dielectric heating during the different phases of the production needs to be considered too. Nevertheless, the dielectric properties of the processed material needs to be known for the design of an appropriate microwave applicator. When looking at the first stage in the production, the stabilization stage of the PAN fiber, the important data about the dielectric properties is very limited in literature. For this reason, first in-situ temperature-dependent measurements of the dielectric properties during the stabilization stage are presented. The impact of raising temperatures and chemical reactions on the dielectric properties of the heated PAN fiber is discussed. Secondly, the steps taken to set up the reaction kinetics from the dielectric loss point of view are given. This enables determination of the reaction degree as a function of the measured dielectric loss for the first time. The established correlation opens the potential for the application to processes such as an in-situ quality determination. The strong temperature impact on the process is shown, and reaction kinetics are analyzed accordingly. In a final third step, a heat transfer model is presented. It utilizes the evaluated reaction kinetics data and microwave heating, creating a first modelling approach for monitoring and controlling the desired fiber temperature, leading towards an online process.
Role of Plasticizers on PHB/bio-TPE Blends Compatibilized by Reactive Extrusion
Authors: Samaniego Kerly , Matos Armando , Sánchez-Safont Estefanía , Candal María V. , Lagaron Jose M. , Cabedo Luis , Gamez-Perez Jose
Published: February 2022

Poly(hydroxybutyrate) (PHB) is a biopolymer biologically synthesized by controlled bacterial fermentation from a wide variety of microorganisms. PHB is proposed as a potential green alternative to commonly used plastics in packaging, due to its biodegradability and biocompatibility. However, if PHB is to replace commodities, it has some limitations regarding its thermo-mechanical performance to overcome. Among them are its critically the low toughness values at room temperature and poor thermoforming ability. With the aim of overcoming these weaknesses, in this work, blends of PHB with the addition of a biodegradable thermoplastic elastomer (bio-TPE) were prepared and evaluated. Films of such compounds were made by cast extrusion. In order to enhance the compatibility of both polymers during the extrusion process, three different reactive agents (poly-hexametylene diisocianate, triglycidyl isocyanurate, and Joncryl® ADR-4368) were assessed. The morphology and mechanical- and thermal properties of the films obtained were analyzed. In addition, the thermoforming ability of the produced films was evaluated. The results show that the plasticizers present in the bio-TPE interacted with the reactive agents, making them chemical competitors and altering the outcome of the blends.
Neural Metric Factorization for Recommendation
Authors: Sun Xiaoxin , Gong Liqiu , Han Zhichao , Zhao Peng , Yu Junchao , Wang Suhua
Published: February 2022

All current recommendation algorithms, when modeling user–item interactions, basically use dot product. This dot product calculation is derived from matrix factorization. We argue that an inherent drawback of matrix factorization is that latent semantic vectors of users or items sometimes do not satisfy triangular inequalities, which may affect the performance of the recommendation. Recently, metric factorization was proposed to replace matrix factorization and has achieved some improvements in terms of recommendation accuracy. However, similar to matrix factorization, metric factorization still uses a simple, linear fashion. In this paper, we explore leveraging nonlinear deep neural networks to realize Euclidean distance interaction between users and items. We propose a generic Neural Metric Factorization Framework (NMetricF), which learns representations for users and items by incorporating Euclidean metric factorization into deep neural networks. Extensive experiments on six real-world datasets show that, compared to the previous recommendation algorithms based purely on rating data, NMetricF achieves the best performance.
On Estimating the Parameters of the Beta Inverted Exponential Distribution under Type-II Censored Samples
Authors: Aldahlan Maha A. , Bakoban Rana A. , Alzahrani Leena S.
Published: February 2022

This article aims to consider estimating the unknown parameters, survival, and hazard functions of the beta inverted exponential distribution. Two methods of estimation were used based on type-II censored samples: maximum likelihood and Bayes estimators. The Bayes estimators were derived using an informative gamma prior distribution under three loss functions: squared error, linear exponential, and general entropy. Furthermore, a Monte Carlo simulation study was carried out to compare the performance of different methods. The potentiality of this distribution is illustrated using two real-life datasets from difference fields. Further, a comparison between this model and some other models was conducted via information criteria. Our model performs the best fit for the real data.
Synchronization of Nonlinear Complex Spatiotemporal Networks Based on PIDEs with Multiple Time Delays: A P-sD Method
Authors: Dai Jiashu , Yang Chengdong
Published: February 2022

This paper studies the synchronization control of nonlinear multiple time-delayed complex spatiotemporal networks (MTDCSNs) based on partial integro-differential equations. Firstly, dealing with an MTDCSN with time-invariant delays, P-sD control is employed and the synchronization criteria are obtained in terms of LMIs. Secondly, this control method is further used in an MTDCSN with time-varying delays. An example illustrates the effectiveness of the proposed methods.
Numerical Method for Solving of the Anomalous Diffusion Equation Based on a Local Estimate of the Monte Carlo Method
Authors: Saenko Viacheslav V. , Kovalnogov Vladislav N. , Fedorov Ruslan V. , Generalov Dmitry A. , Tsvetova Ekaterina V.
Published: February 2022

This paper considers a method of stochastic solution to the anomalous diffusion equation with a fractional derivative with respect to both time and coordinates. To this end, the process of a random walk of a particle is considered, and a master equation describing the distribution of particles is obtained. It has been shown that in the asymptotics of large times, this process is described by the equation of anomalous diffusion, with a fractional derivative in both time and coordinates. The method has been proposed for local estimation of the solution to the anomalous diffusion equation based on the simulation of random walk trajectories of a particle. The advantage of the proposed method is the opportunity to estimate the solution directly at a given point. This excludes the systematic component of the error from the calculation results and allows constructing the solution as a smooth function of the coordinate.
Multiscale Balanced-Attention Interactive Network for Salient Object Detection
Authors: Yang Haiyan , Chen Rui , Deng Dexiang
Published: February 2022

The purpose of saliency detection is to detect significant regions in the image. Great progress on salient object detection has been made using from deep-learning frameworks. How to effectively extract and integrate multiscale information with different depths is an open problem for salient object detection. In this paper, we propose a processing mechanism based on a balanced attention module and interactive residual module. The mechanism addressed the acquisition of the multiscale features by capturing shallow and deep context information. For effective information fusion, a modified bi-directional propagation strategy was adopted. Finally, we used the fused multiscale information to predict saliency features, which were combined to generate the final saliency maps. The experimental results on five benchmark datasets show that the method is on a par with the state of the art for image saliency datasets, especially on the PASCAL-S datasets, where the MAE reaches 0.092, and on the DUT-OMROM datasets, where the F-measure reaches 0.763.
FMEA in Smartphones: A Fuzzy Approach
Authors: Kadena Esmeralda , Koçak Sinan , Takács-György Katalin , Keszthelyi András
Published: February 2022

Smartphones are attracting increasing interest due to how they are revolutionizing our lives. On the other hand, hardware and software failures that occur in them are continually present. This work aims to investigate these failures in a typical smartphone by collecting data from a class of people. Concerns have been raised that call into question the efficiency of applied methods for identifying and prioritizing the potential defects. The widely used hybridized engineering method, Fuzzy Failure Mode and Effect Analysis (F-FMEA), is an excellent approach to solving these problems. The F-FMEA method was applied to prioritize the potential failures based on their Severity (S), expected Occurrence (O), and the likelihood of Detectability (D). After collecting failure data from different users on a selected smartphone, two well-known defuzzification methods facing the Risk Priority Number (RPN) in F-FMEA were applied. Despite this interest, to the best of our knowledge, no one has studied smartphone failures with a technique that combines the results of different fuzzy applications. Thus, to combine the results of the derived fuzzy subsystems for the average value, we suggest a summative defuzzification method. Our findings indicate that F-FMEA with a summative defuzzification procedure is a clear improvement on the F-FMEA method. Even though the summation method modifies close results of the defuzzification one, it was shown that it provides more accurate results.
A Hybrid Localized Meshless Method for the Solution of Transient Groundwater Flow in Two Dimensions
Authors: Wang Qiang , Kim Pyeoungkee , Qu Wenzhen
Published: February 2022

In this work, a hybrid localized meshless method is developed for solving transient groundwater flow in two dimensions by combining the Crank–Nicolson scheme and the generalized finite difference method (GFDM). As the first step, the temporal discretization of the transient groundwater flow equation is based on the Crank–Nicolson scheme. A boundary value problem in space with the Dirichlet or mixed boundary condition is then formed at each time node, which is simulated by introducing the GFDM. The proposed algorithm is truly meshless and easy to program. Four linear or nonlinear numerical examples, including ones with complicated geometry domains, are provided to verify the performance of the developed approach, and the results illustrate the good accuracy and convergency of the method.
Analysis of Single-Leg Hopping in Long-Term Treated Patients with Neurological Wilson’s Disease: A Controlled Pilot Study
Authors: Hefter Harald , Samadzadeh Sara , Rosenthal Dietmar , Tezayak Osman
Published: February 2022

Background and Objectives: In long-term treated patients with neurological Wilson’s disease, the ability to perform single-leg hopping was analyzed to quantify motor deficits. Materials and Methods: Twenty-nine long-term treated Wilson patients had to stand on one leg for at least 3 s and then perform at least five consecutive hops on this leg. Ground reaction forces and temporal patterns of hopping were recorded using an Infotronic® walking system, which consists of soft tissue shoes with a solid, but flexible plate containing eight force transducers allowing measurement of ground reaction forces (GRF) and temporal patterns of foot ground contact. Parameters of hopping were correlated with clinical scores and parameters of copper metabolism and liver enzymes. Patients’ hopping data were compared with those of an age- and sex-matched control group. Results: Five severely affected Wilson patients were unable to hop. Time to the peak was significantly (p < 0.03) shorter in the remaining 24 patients compared to controls, but there was no difference in hopping frequency, the amplitude of ground forces and duration of foot contact. Twelve patients produced a second, sharp, initial “impact” force peak during ground contact in addition to the usual “active” force peak. Variability of the amplitude of the “active” peak was significantly inversely correlated with urinary copper elimination. Conclusions: The majority of long-term treated patients with neurological Wilson’s disease was able to perform single-leg hopping. The presence of a sharp initial “impact” peak in the GRF-curves of hopping may indicate a mild deficit of limb/trunk coordination and subclinical cerebellar impairment.
Efficacy of Minimally Invasive Trans-Sacral Canal Plasty between Patients with and without Failed Back Surgery Syndrome
Authors: Funao Haruki , Yokosuka Kimiaki , Ukai Junichi , Nakanishi Kazuo , Paku Masaaki , Tomita Takashi , Hoshino Masahiro , Saito Takanori , Ishii Ken , Sato Koji
Published: February 2022

Background and Objectives: Clinicians are required to manage a growing number of elderly patients with several medical comorbidities, and invasive surgical treatments are sometimes not advisable for these patients. The aim of this study was to evaluate the efficacy of minimally invasive intraspinal canal treatment, trans-sacral canal plasty (TSCP), for patients with and without failed back surgery syndrome (FBSS). Materials and Methods: A multicenter analysis was conducted. TSCP was performed in patients with chronic low back pain and leg pain due to lumbar spinal disorders. An adhesiolysis by TSCP was carried out, then a mixture of steroid and local anesthesia was injected. Visual Analog Scales (VAS) for low back pain and leg pain, and complications were evaluated. Results: A total of 271 patients with a minimum 6-month follow-up were enrolled. There were 80 patients who had a history of previous lumbar spinal surgery (F group), and 191 patients without previous lumbar spinal surgery (N group). There were no significant differences in sex and age between the two groups. VAS scores for low back pain (N group/F group) preoperatively, immediately postoperatively, and 1 month, 3 months and 6 months postoperatively, were 51/52 mm, 24/26 mm, 33/34 mm, 30/36 mm, and 30/36 mm, respectively. VAS scores for leg pain were 69/67 mm, 28/27 mm, 39/41 mm, 36/43 mm, and 32/40 mm, respectively. Both VAS scores for low back pain and leg pain were significantly decreased from baseline to final follow-up in both groups (p < 0.01). However, VAS scores for leg pain at 3 months and 6 months postoperatively were significantly higher in F group (p < 0.05). There were three catheter breakages (2/3 in F group), and one dural tear in F group. Conclusions: TSCP significantly reduced both VAS scores for low back and leg pain in patients with and without FBSS. However, co-existence of intractable epidural adhesion might be associated with less improvement in FBSS.
Permeate Flux in Ultrafiltration Processes—Understandings and Misunderstandings
Authors: Field Robert W. , Wu Jun Jie
Published: February 2022

Concentration polarization refers to the rapid emergence of concentration gradients at a membrane/solution interface resulting from selective transfer through the membrane. It is distinguishable from fouling in at least two ways: (1) the state of the molecules involved (in solution for concentration polarization, although no longer in solution for fouling); and (2) by the timescale, normally less than a minute for concentration polarization, although generally at least two or more orders of magnitude more for fouling. Thus the phenomenon of flux decline occurring over a timescale of tens of minutes should not be attributed to concentration polarization establishing itself. This distinction and a number of questions surrounding modelling are addressed and clarified. There are two paradigmatic approaches for modelling flux, one uses the overall driving force (in which case allowance for osmotic effects are expressed as additional resistances) and the other uses the net driving force across the separating layer or fouled separating layer, although often the two are unfortunately comingled. In the discussion of flux decline models’ robust approaches for the determination of flux-time relationships, including the integral method of fouling analysis, are discussed and various concepts clarified. The final section emphases that for design purposes, pilot plant data are vital.
Preparation and Separation Properties of Electrospinning Modified Membrane with Ionic Liquid Terminating Polyimide/Polyvinylpyrrolidone@Polydopamine
Authors: Qi Peng , Jia Hongge , Xu Shuangping , Wang Qingji , Su Guiming , Yang Guoxing , Zhang Mingyu , Qu Yanqing , Pei Fuying
Published: February 2022

In this paper, superhydrophilic polyimide (PI) membranes were prepared using the electrostatic spinning method, capped with a hydrophilic ionic liquid (IL), and blended with polyvinylpyrrolidone (PVP). Using this preparation, the surface of the fiber membranes was coated in polydopamine (PDA) by means of an in-growth method. Scanning electron micrographs showed prepared blend films can form continuous fibers, for whom the distributions of diameter and pore were uniform. Post-modification (carried out by adding hydrophilic substances), the ability of the membrane surface to adhere to water was also significantly improved. The water contact angle was reduced from 128.97 ± 3.86° in unmodified PI to 30.26 ± 2.16°. In addition, they displayed a good separation effect on emulsified oil/water mixtures. The membrane flux reached a maximum value of 290 L·m−2·h−1, with a maximum separation efficiency reached of more than 99%. After being recycled 10 times, the separation efficiency maintained a level exceeding 95%. The purpose of this study is to demonstrate the simplicity and efficiency of this experiment, thereby providing new ideas for the future application of membrane separation technology in wastewater treatment.
Rejuvenation-to-Relaxation Transition Induced by Elastostatic Compression and Its Effect on Deformation Behavior in a Zr-Based Bulk Metallic Glass
Authors: Cui Jingxian , Luo Qiang , Di Siyi , Zhang Zhengguo , Shen Baolong
Published: February 2022

The effect of uniaxial elastostatic compression on the deformation behavior of the Zr41.2Ti13.8Cu12.5Ni10Be22.5 (Vit1) bulk metallic glass (BMG) was reported. The as-cast alloy was pre-compressed under various time (20, 40 and 60 h) at a preloading level of 87% of its yield strength. It was found that elastostatic compression can lead to structural rejuvenation or relaxation depending on the pre-compression time. Elastostatic compression, for 40 h, increased the free volume and improved the plasticity of the BMGs from 1.4% to 3.4%, but preloading for 60 h decreased the free volume and worsened the plasticity. In addition, the heterogeneous structure evolution during creep deformation has been analyzed by the Maxwell-Voigt model with two Kelvin units, revealing that more (less) defects with larger size are activated after elastostatic compression treatment for 40 h (60 h). This work sheds new light on the correlation between heterogeneous structure and plasticity/creep behaviors of Zr-based BMGs.
Finite Element Analysis on Welding-Induced Distortion of Automotive Rear Chassis Component
Authors: Kim Jin-Jae , Bae Moonki , Hong Myoung-Pyo , Kim Young-Suk
Published: February 2022

Welding-induced distortion is a major concern for the industrial joining practice. The welding-induced distortion at the weldment between the coupled torsion beam axle (CTBA) of the automotive rear chassis parts and trailing arm connected to the wheel hub axle module seriously affects the tow angle, camber angle, and caster of the wheel axle. In this paper, the welding process between CTBA and trailing arm was numerically analyzed via SYSWELD (i.e., a finite element analysis code), using the material properties predicted via J-MatPro SW, material properties software, considering the thermo-mechanical-metallurgical properties of materials. From the numerical study for the weldment of CTBA and trailing arm, we predicted the welding and thermal distortions, temperature variation, microstructure, and residual stress at the concerned area. As a result, the temperature of the welded area was predicted between 102 °C and 840 °C at the end of weldment and converged to room temperature after 1000 s. The maximum portion of the martensite structure at the welded area was expected to be 55%. The expected distortions of the trailing arm after the weldment were 0.52 mm, −1.47 mm, and 0.44 mm in the x, y, and z-directions, respectively. Finally, the limitations of this research and recommendations are presented.
Plasma Metabolite Signature Classifies Male LRRK2 Parkinson’s Disease Patients
Authors: Dong Chen , Honrao Chandrashekhar , Rodrigues Leonardo O. , Wolf Josephine , Sheehan Keri B. , Surface Matthew , Alcalay Roy N. , O’Day Elizabeth M.
Published: February 2022

Parkinson’s disease (PD) is a progressive neurodegenerative disease, causing loss of motor and nonmotor function. Diagnosis is based on clinical symptoms that do not develop until late in the disease progression, at which point the majority of the patients’ dopaminergic neurons are already destroyed. While many PD cases are idiopathic, hereditable genetic risks have been identified, including mutations in the gene for LRRK2, a multidomain kinase with roles in autophagy, mitochondrial function, transcription, molecular structural integrity, the endo-lysosomal system, and the immune response. A definitive PD diagnosis can only be made post-mortem, and no noninvasive or blood-based disease biomarkers are currently available. Alterations in metabolites have been identified in PD patients, suggesting that metabolomics may hold promise for PD diagnostic tools. In this study, we sought to identify metabolic markers of PD in plasma. Using a 1H-13C heteronuclear single quantum coherence spectroscopy (HSQC) NMR spectroscopy metabolomics platform coupled with machine learning (ML), we measured plasma metabolites from approximately age/sex-matched PD patients with G2019S LRRK2 mutations and non-PD controls. Based on the differential level of known and unknown metabolites, we were able to build a ML model and develop a Biomarker of Response (BoR) score, which classified male LRRK2 PD patients with 79.7% accuracy, 81.3% sensitivity, and 78.6% specificity. The high accuracy of the BoR score suggests that the metabolomics/ML workflow described here could be further utilized in the development of a confirmatory diagnostic for PD in larger patient cohorts. A diagnostic assay for PD will aid clinicians and their patients to quickly move toward a definitive diagnosis, and ultimately empower future clinical trials and treatment options.
Lipidome Alterations following Mild Traumatic Brain Injury in the Rat
Authors: Gier Eric C. , Pulliam Alexis N. , Gaul David A. , Moore Samuel G. , LaPlaca Michelle C. , Fernández Facundo M.
Published: February 2022

Traumatic brain injury (TBI) poses a major health challenge, with tens of millions of new cases reported globally every year. Brain damage resulting from TBI can vary significantly due to factors including injury severity, injury mechanism and exposure to repeated injury events. Therefore, there is need for robust blood biomarkers. Serum from Sprague Dawley rats was collected at several timepoints within 24 h of mild single or repeat closed head impacts. Serum samples were analyzed via ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) in positive and negative ion modes. Known lipid species were identified through matching to in-house tandem MS databases. Lipid biomarkers have a unique potential to serve as objective molecular measures of injury response as they may be liberated to circulation more readily than larger protein markers. Machine learning and feature selection approaches were used to construct lipid panels capable of distinguishing serum from injured and uninjured rats. The best multivariate lipid panels had over 90% cross-validated sensitivity, selectivity, and accuracy. These mapped onto sphingolipid signaling, autophagy, necroptosis and glycerophospholipid metabolism pathways, with Benjamini adjusted p-values less than 0.05. The novel lipid biomarker candidates identified provide insight into the metabolic pathways altered within 24 h of mild TBI.
“Leaky Gut” as a Keystone of the Connection between Depression and Obstructive Sleep Apnea Syndrome? A Rationale and Study Design
Authors: Gawlik-Kotelnicka Oliwia , Margulska Aleksandra , Gabryelska Agata , Sochal Marcin , Białasiewicz Piotr , Strzelecki Dominik
Published: February 2022

Obstructive sleep apnea (OSA) and depression are highly comorbid. Immune alterations, oxidative stress or microbiota dysfunction have been proposed as some mechanisms underlying this association. The aim of the proposed study is to assess the severity and profile of OSA and depressive symptoms in the context of serum microbiota metabolites, biomarkers of intestinal permeability, inflammation and oxidative stress in adult patients diagnosed with OSA syndrome. The study population consists of 200 subjects. An apnoea-hypopnoea index ≥ 5/hour is used for the diagnosis. Depressive symptoms are assessed with Beck Depression Inventory. Measured serum markers are: tumour necrosis factor–alpha and interleukin-6 for inflammation, total antioxidant capacity and malondialdehyde concentration for oxidative stress, zonulin, calprotectin, lipopolisaccharide-binding protein and intestinal fatty acids-binding protein for intestinal permeability. All of the above will be measured by enzyme-linked immunosorbent assay (ELISA). Associations between clinical symptoms profile and severity and the above markers levels will be tested. It would be valuable to seek for overlap indicators of depression and OSA to create this endophenotype possible biomarkers and form new prophylactic or therapeutic methods. The results may be useful to establish a subpopulation of patients sensitive to microbiota therapeutic interventions (probiotics, prebiotics, and microbiota transplantation).
A Thermopile Infrared Sensor Array Pixel Monolithically Integrated with an NMOS Switch
Authors: Li Hongbo , Zhang Chenchen , Xu Gaobo , Ding Xuefeng , Ni Yue , Chen Guidong , Chen Dapeng , Zhou Na , Mao Haiyang
Published: February 2022

In this article, we present the design, fabrication, and characterization of a thermopile infrared sensor array (TISA) pixel. This TISA pixel is composed of a dual-layer p+/n- poly-Si thermopile with a closed membrane and an n-channel metal oxide semiconductor (NMOS) switch. To address the challenges in fabrication through the 3D integration method, the anode of the thermopile is connected to the drain of the NMOS, both of which are fabricated on the same bulk wafer using a CMOS compatible monolithic integration process. During a single process sequence, deposition, etching, lithography, and ion implantation steps are appropriately combined to fabricate the thermopile and the NMOS simultaneously. At the same time as ensuring high thermoelectric characteristics of the dual-layer p+/n- poly-Si thermopile, the basic switching functions of NMOS are achieved. Compared with a separate thermopile, the experimental results show that the thermopile integrated with the NMOS maintains a quick response, high sensitivity and high reliability. In addition, the NMOS employed as a switch can effectively and quickly control the readout of the thermopile sensing signal through the voltage, both on and off, at the gate of NMOS. Thus, such a TISA pixel fabricated by the monolithic CMOS-compatible integration approach is low-cost and high-performance, and can be applied in arrays for high-volume production.
Deep Learning-Enabled Technologies for Bioimage Analysis
Authors: Rabbi Fazle , Dabbagh Sajjad Rahmani , Angin Pelin , Yetisen Ali Kemal , Tasoglu Savas
Published: February 2022

Deep learning (DL) is a subfield of machine learning (ML), which has recently demonstrated its potency to significantly improve the quantification and classification workflows in biomedical and clinical applications. Among the end applications profoundly benefitting from DL, cellular morphology quantification is one of the pioneers. Here, we first briefly explain fundamental concepts in DL and then we review some of the emerging DL-enabled applications in cell morphology quantification in the fields of embryology, point-of-care ovulation testing, as a predictive tool for fetal heart pregnancy, cancer diagnostics via classification of cancer histology images, autosomal polycystic kidney disease, and chronic kidney diseases.
Investigation of the Contact Characteristics of Silicon–Gold in an Anodic Bonding Structure
Authors: Zhang Lin , Cao Kaicong , Ran Longqi , Yu Huijun , Zhou Wu
Published: February 2022

Anodic bonding is broadly utilized to realize the structure support and electrical connection in the process of fabrication and packaging of MEMS devices, and the mechanical and electrical characteristics of the bonded interface of structure exhibit a significant impact on the stability and reliability of devices. For the anodic bonding structure, including the gold electrode of micro accelerometers, the elastic/plastic contact model of a gold–silicon rough surface is established based on Hertz contact theory to gain the contact area and force of Gauss surface bonding. The trans-scale finite element model of a silicon–gold glass structure is built in Workbench through the reconstruction of Gauss surface net by the reverse engineering technique. The translation load is added to mimic the process of contact to acquire the contact behaviors through the coupling of mechanical and electrical fields, and then the change law of contact resistance is obtained. Finally, the measurement shows a good agreement between the experimental results, theoretical analysis and simulation, which indicates there is almost no change of resistance when the surface gap is less than 20 nm and the resistance is less than 5Ω, while the resistance changes rapidly after the gap exceeds 20 nm.
Pea-Wheat Rotation Affects Soil Microbiota Diversity, Community Structure, and Soilborne Pathogens
Authors: Woo Sheridan Lois , De Filippis Francesca , Zotti Maurizio , Vandenberg Albert , Hucl Pierre , Bonanomi Giuliano
Published: February 2022

Intensive cultivation based on monocultures has a significant impact on ecosystem function, and sustainable agriculture must rely on alternative methods, including crop rotation. On the Canadian prairies, the use of pulse crops is a common practice, but few studies have investigated the impact on soil microorganisms. Here, we studied the effect of pea, wheat, pea–wheat rotation, and fallow in bulk soil bacterial and fungal communities. We characterized soil microbiota by high-throughput sequencing of 16S and 18S rRNA genes for bacteria and eukaryotes. Different crop rotations and fallow significantly modified soil community composition, as well as bacterial and fungal diversity. Pea alone caused a strong reduction of bacterial and fungal richness and diversity compared to wheat, pea–wheat rotation, and fallow. Notably, pea–wheat rotation increased the abundance of Fusarium graminearum compared to other management practices. The bacterial community was less responsive to crop rotation identity compared to the fungal microbiota, and we found minor differences at the phylum level, with an increase in Actinobacteria in fallow and Firmicutes in wheat. In summary, our study demonstrated that rotations alter bulk soil microbial community diversity and composition in Canadian prairies. The frequent use of pea in rotation with wheat should be carefully evaluated, balancing their ecological effects on nitrogen mineralization, water conservation, and impact on beneficial, as well as pathotrophic, fungi.