bluuebunny/crossref_metadata_2025 huggingface dataset:
Fabrication of Optical Fiber Sensors Based on Femtosecond Laser Micro Machining
Authors: Zhou Fengfeng , Jo Seunghwan , Fu Xingyu , Jun Martin Byung-Guk , Tsai Jung-Ting
Published: January 2021

In this research, we proposed fabrication process of optical fiber sensors using femtosecond laser and their applications. A beam of femtosecond laser was focused by an objective lens on the optical fiber. By testing different conditions, a group of machining parameters was found that achieve a minimum machining resolution of 3.2 μm. To ablate the core of the optical fiber, which is buried deep inside the cladding, precisely, part of the cladding was removed to expose the core as close as possible to the air. By making a complex pattern to modify the optical path of the laser inside an optical fiber, a sensitivity of 942.8 to 1015.6 nm/RIU was obtained for liquid refractive index sensing. For another sensor, a sensitivity of 1.38 × 105 nm/RIU was obtained which is high enough to detect small amount of refractive index change of air. It is known to be the first time that we fabricated a complex microstructure in an optical fiber to modify the propagation of the light using femtosecond laser. This research shows the possibility of a complex modification of light in an optical fiber using laser machining.
Understanding and Evaluating Naive Diagnostics Algorithms Applicable in Multistage Manufacturing From a Risk Management Perspective
Authors: Dadfarnia Mehdi , Sharp Michael , Sprock Timothy
Published: January 2021

The world has entered a state of unprecedented access to machine intelligence algorithms, where the ease of deployment has created a scenario where nearly every facet of life and industry has been affected by AI. Especially within industry, where the options for enacting AI systems are wide and varied, the choice of which system will work best for a given application can be daunting. Understanding when, where, and why to apply a particular algorithm can provide competitive advantage on effectiveness as well as greater trust and justification when using the algorithms’ outputs. This paper examines multistage manufacturing processes, where system complexity can greatly influence the burden of creating custom tailored monitoring solutions. Such barriers have encouraged many manufacturing small and medium enterprises (SME) to look towards generic ‘black box’ commercial software solutions, although they may lack the sufficient expertise to objectively determine which product best meets their requirements. Some of the considerations faced by SMEs are identifying tools that can successfully be deployed alongside a potential lack of sensor coverage and/or the desire for rapid system reconfiguration to accommodate smaller custom batch production sizes. In these environments, detailed analytics-based solutions are often not feasible for production equipment monitoring. This paper provides a procedure for assessing the suitability of various tools or algorithms used to evaluate production process performance based on product quality output. This paper also presents a preliminary comparative example study of several algorithms to demonstrate this process and evaluate the selected algorithms.
Class Incremental Fault Detection and Diagnosis With Unlabeled Condition Monitoring Data
Authors: Peng Xiaomeng , Jin Xiaoning , Duan Shiming , Sankavaram Chaitanya
Published: January 2021

Data-driven methods for fault detection and diagnostics (FDD) require a large amount of labeled data and knowledge about complete failure modes set to train a reliable classifier as well as require the same label space in an online testing phase. Typical supervised classifiers in FDD can only predict precedented faults, limiting their performance in identifying unprecedented failure modes in on-line testing data. In addition, in most applications, it may be expensive and time-consuming to obtain sufficient labeled samples. This study focuses on fault detection and diagnosis without sufficient labels or prior knowledge of the complete set of failure modes. This paper proposes a novel FDD framework using active learning and semi-supervised learning to detect both precedented and unprecedented failures with minimum labeling effort. The effectiveness of proposed approach is demonstrated and validated using a synthetic condition monitoring dataset.
Thermal Modeling in Metal Additive Manufacturing Using Graph Theory: Experimental Validation With In-Situ Infrared Thermography Data From Laser Powder Bed Fusion
Authors: Yavari Reza , Williams Richard , Cole Kevin , Hooper Paul , Rao Prahalad
Published: January 2021

The objective of this work is to provide experimental validation of the graph theory approach for predicting the thermal history in additively manufactured parts that was recently published in the ASME transactions. In the present paper the graph theory approach is validated with in-situ infrared thermography data in the context of the laser powder bed fusion (LPBF) additive manufacturing process. We realize this objective through the following three tasks. First, two types of test parts (stainless steel) are made in two corresponding build cycles on a Renishaw AM250 LPBF machine. The intent of both builds is to influence the thermal history of the part by changing the cooling time between melting of successive layers, called interlayer cooling time. Second, layer-wise thermal images of the top surface of the part are acquired using an in-situ a priori calibrated infrared camera. Third, the thermal imaging data obtained during the two builds were used to validate the graph theory-predicted surface temperature trends. Furthermore, the surface temperature trends predicted using graph theory are compared with results from finite element analysis. As an example, for one the builds, the graph theory approach accurately predicted the surface temperature trends to within 6% mean absolute percentage error, and approximately 14 Kelvin root mean squared error of the experimental data. Moreover, using the graph theory approach the temperature trends were predicted in less than 26 minutes which is well within the actual build time of 171 minutes.
MSEC: A Quantitative Retrospective
Authors: Sexton Thurston , Brundage Michael P. , Dima Alden , Sharp Michael
Published: January 2021

The ASME 2020 Manufacturing Science and Engineering Conference (MSEC) is the 15th annual meeting organized by the Manufacturing Engineering Division (MED) of ASME. MED and ASME MSEC focuses on manufacturing sciences, technology, and applications, including machining, materials processing, sensing, robotics, manufacturing system dynamics, and production optimization. As the conference has grown and evolved from its inception, it can be difficult to intuitively visualize and discuss the broad range of research topics covered by the MSEC community or to intuitively ascertain their evolution throughout time. This paper discusses a methodology to quantitatively model research communities within bodies of literature — specifically, the relative change of relevant topics within AMSE MSEC conference papers through time, from 2006 through 2018. The goal of this work is to not only present how research in MSEC has shifted over time, but in a broader sense to provide a discussion on how others can interpret results so that similar analysis can be produced within other research communities. This methodology can be used to identify overlap of communities, monitor growth or stagnation within the communities, to aid in developing new symposiums and communities of interest, or even to dictate future standards needs by looking at research trends and subsequent standard development.
Discrete Element Modeling of Scraping Process and Quantification of Powder Bed Quality for SLM
Authors: Mandloi Kuldeep , Amrapurkar Parth , Cherukuri Harish P.
Published: January 2021

In selective laser melting (SLM) and selective laser sintering (SLS) additive manufacturing techniques, the powder spreading process plays a key role in the quality of the manufactured parts. Some of the important parameters that influence the quality of the powder bed are the powder particle size distribution, spreader-type (roller or blade), spreader speed, size and shape of the particles. In this work, we use the discrete element method to study the effect of these parameters on the quality of the powder bed. The interactions between the particles is modeled using Hertz-Mindlin contact model as well as Hertz-Mindlin with JKR contact model with the latter being used for studies of the effect of cohesiveness of particles on powder bed quality. The Dynamic Repose Angle (DRA) is used for validating the numerical models. Our studies differ from the previous studies in that we have introduced quantitative measures for powder bed quality in the form of Discretized Volume Fraction (DVF) and Particle Flow Rate (PFR) for the layering process. With the help of these quantities, we studied various factors that affect powder bed quality: cohesiveness of the particles, spreader shape, particle size and shape, and the distribution of particle sizes. Our results indicate that as DVF and PFR decrease and DRA increases, the potential for cavities and shifting defects increases due to increase in cohesiveness. Use of fixed particle size in the simulations leads to higher DRA than when a normal distribution of particle sizes is considered. Our results show that the roller geometry provides better bed quality as compared to the blade type geometry.
A Vibration-Assisted Separation Method for Constrained-Surface-Based Stereolithography
Authors: Xu Yang , Zhu Yizhen , Sun Yifeng , Jin Jie , Chen Yong
Published: January 2021

For the bottom-up based stereolithography (SL) process, a separation process is required to detach the newly cured layer from the constrained surface in order to accomplish the fabrication of the current layer. Excessive separation force will cause damage to the built layers and the constrained surface. Different surface coatings, platform motions including tilting and sliding, and the utilization of oxygen-permeable films have been proposed to address the separation-related problems. Among these approaches, there is a limited study on the vibration-assisted (VA) separation method to reduce the separation force. The underlying mechanism of the VA-separation-based method remains unexplored for the SL-related additive manufacturing, and the best way to use VA separation in the bottom-up based SL process is still unclear. In this paper, a new VA separation design for the bottom-up SL process is presented. A prototype system has been built to study the VA separation mechanism in SL. Experiments on the separation performance under different parameters including vibration frequency, pre-stress level, and exposure area were conducted. Based on the collected separation force data, an analytical model based on the mechanics of fatigue fracture was built. The separation behaviors related to different shape sizes and topologies were also studied and compared. The results showed that the separation force in SL was significantly reduced using the VA-separation-based method. Furthermore, the relationship between the separation force and the separation time conforms to the stress-based fatigue model well. This study provides insights on how to choose process parameters by considering the trade-offs between separation force and building efficiency.
Nano-Scale Hardness and Abrasion Resistance of Directed Energy Deposited Co-Cr-Mo Biomedical Alloy
Authors: Liu Michael , Kuttolamadom Mathew
Published: January 2021

The objective of this work is to investigate the hardness and abrasion resistance of a cobalt-chromium-molybdenum (Co-Cr-Mo) alloy fabricated via directed energy deposition (DED) additive manufacturing. Being a bio-compatible alloy, Co-Cr-Mo is commonly used in biomedical implants. Hence, its small-scale tribological behavior needs to be characterized, especially when fabricated via a newer process such as DED; thus the focus at nano scale. For this, a design of experiments was utilized to investigate the relevant process parameter design space for the laser engineered net shaping (LENS) process, with an objective to manufacture structurally-integral samples. Further, the effects of these process parameters were correlated with the resulting material properties at the nanoscale (viz., hardness modulus, and abrasion resistance). Results showed certain samples with competitively-high corresponding properties when compared to traditional made Co-Cr-Mo alloys, but with a large spread in properties, as is typical for such manufacturing processes. Also, microstructural characteristics were in line with traits observed when fabricating via traditional methods. Especially worth noting is the formation of metal carbides at the boundaries of cell-shaped grains; this causes a depletion of carbon at the center of the grain and thin carbides at the boundaries, thus significantly affecting the composite properties of the material. Altogether, this work shows the promise of using LENS to fabricate tailored structurally-integral Co-Cr-Mo alloys.
Design and Evaluation of Human-Machine Interface for NEXUS: A Custom Microassembly System
Authors: Wei Danming , Hall Mariah B. , Sherehiy Andriy , Kumar Das Sumit , Popa Dan O.
Published: January 2021

Microassembly systems utilizing precision robotics have long been used for realizing 3-dimensional microstructures such as microrobots. Prior to assembly, such components are fabricated using Micro-Electro-Mechanical-System (MEMS) technology. The microassembly system then directs a microgripper through automated or human-controlled pick-and-place operations. In this paper, we describe a novel custom microassembly system, named NEXUS. The NEXUS integrates multi-degree of freedom (DOF) precision positioners, microscope computer vision, and micro-scale process tools such as a microgripper and vacuum tip. A semi-autonomous human-machine interface (HMI) is programmed by NI LabVIEW® to allow the operator to interact with the microassembly system. The NEXUS human-machine interface includes multiple functions, such as positioning, target detection, visual servoing, and inspection. The microassembly system’s HMI was used by operators to assemble various 3-dimensional microrobots such as the Solarpede, a novel light-powered stick-and-slip mobile microcrawler. Experimental results are reported in this paper that evaluate the system’s semi-autonomous capabilities in terms of assembly rate and yield and compare them to purely teleoperated assembly performance. Results show that the semi-automated capabilities of the microassembly system’s HMI offer a more consistent assembly rate of microrobot components.
Laser Sharpening of Carbon Fiber Microelectrode Arrays for Brain Recording
Authors: Dong Tianshu , Chen Lei , Shih Albert
Published: January 2021

Microwire microelectrode arrays (MEAs) are implanted in the brain for recording neuron activities to study the brain functioning mechanism. Among various microwire materials that had been applied, carbon fiber is outstanding due to its small footprint (6–7 μm), relatively high Young’s modulus, and low electrical resistance. Tips of microwire in MEAs are often sharpened to reduce insertion force. Currently, carbon fiber MEAs are sharpened with either torch burning, which can only give a uniform length of wires in an array, or electrical discharge machining (EDM), which requires circuit connection with each single carbon fiber. The sharp tip results from intense burning induced by a flame or spark, leading to poor repeatability and controllability of the sharp tip geometry. In this paper, a laser-based, non-contact carbon fiber sharpening method is proposed, which enables controllable and repeatable production of carbon fiber MEAs of custom electrode lengths, insulation stripping lengths, and sharpened tips. Path of laser movement is designed according to desired array pattern. Variation in tip geometry can be accomplished by changing laser output power and moving speed. Test with different laser parameters (output power and moving speed) were conducted. Tip sharpening results were evaluated and analyzed in terms of tip geometry and insulation stripping length. Results showed that to achieve the desired MEA with sharper tip and shorter insulation stripping length, a higher laser power with faster moving speed is preferred.
A Robotic Cell for Embedding Prefabricated Components in Extrusion-Based Additive Manufacturing
Authors: Yoon Yeo Jung , Almeida Oswin G. , Shembekar Aniruddha V. , Gupta Satyandra K.
Published: January 2021

By attaching a material extrusion system to a robotic arm, we can deposit materials onto complex surfaces. Robotic manipulators can also maximize the task utility by performing other tasks such as assembly or surface polishing when they are not in use for the AM process. We present a robotic cell for embedding prefabricated components in extrusion-based AM. The robotic cell consists of two 6 degrees of freedom (DOF) robots, an extrusion system, and a gripper. One robot is used for printing a part, and the other robot takes a support role to pick and place the prefabricated component and embed it into the part being printed. After the component is embedded, AM process resumes, and the material is deposited onto the prefabricated components and previously printed layers. We illustrate the capabilities of the system by fabricating three objects.
Top-Down Processing Towards Ångström-Thin Two-Dimensional (2D) Elemental Metals
Authors: Rubayat-E Tanjil Md , Agbakansi Stanley , Suero Keegan Phayden , Douglas Ossie , Jeong Yunjo , Yin Zhewen , Panaccione Wyatt , Wang Michael Cai
Published: January 2021

Two-dimensional (2D) materials have recently garnered significant interest due to their novel and emergent properties. A plethora of 2D materials have been discovered and intensively studied, such as graphene, hexagonal boron nitride, transitionmetal dichalcogenides (TMDCs), and other metallic compound MXenes (nitrides, phosphides, and hydroxides), as well as elemental 2D materials (borophene, germanene, phosphorene, silicene, etc.). Considering the widespread interest in conventional van der Waals 2D materials, two-dimensional metallic nanosheets (2DMNS), a recent addition to the 2D materials family, have exhibited diverse potential spanning optics, electronics, magnetics, catalysis, etc. However, the close-packed, non-layered structure and non-directional, isotropic bonding of metallic materials make it difficult to access metals in their 2D forms, unlike 2D van der Waals materials, which have intrinsically layered structure (strong in-plane bonding in addition to the weak interlayer interaction). Until now, conventional top-down and bottom-up synthesis schemes of these 2DMNS have encountered various limitations such as precursor availability, substrate incompatibility, difficulty of control over thickness and stoichiometry, limited thermal budget, etc. To overcome these manufacturing limitations of 2DMNS, here we report a facile, rapid, large-scale, and cost-effective fabrication technique of nanometer-scale copper (Cu) 2DMNS via iterative rolling, folding, and calendering (RFC) that is readily generalizable to other conventional elemental metallic materials. Overall, we successfully show a scalable fabrication technique of 2DMNS.
Machine Learning Based Novelty Detection Methods for Progressive Stamping Process Health Monitoring
Authors: Qiu Tianchen , Lai Xingjian , Ni Jun
Published: January 2021

Progressive (die) stamping is a widely used sheet metal forming process in the manufacturing of automobiles and consumer electronics. Current literature suggests limited knowledge of online health monitoring and fault detection capability. This paper aims to propose a data-driven, empirical approach for diagnosing potential abnormal health conditions of the progressive stamping machine. The proposed signal features and selected novelty detection algorithm work together for fault diagnosis and compensate for the lack of theoretical knowledge of this high-volume high-speed production process. Novelty detection, usually approached within the framework of one-class classification, demonstrates luminous potential applications in machine system health monitoring. During progressive stamping process, there are abundant normal operating data while it is unclear how complex machine health factors together affect the feature signals. The task is to recognize the abnormality by recognizing the significance of how testing data differ from training data by forming a decision boundary from normal behaving training data only. Through literature review, One-Class Support Vector Machine (OCSVM) is selected as the main algorithm for this application. Through applying kernel tricks, the hyperplane can be used to classify nonlinear machine health indictors. OCSVM also utilizes sparse supporting vectors to form a computationally efficient decision boundary and can therefore be used for online fault detections. In this study, the proposed novelty detection approach is explained and successfully implemented based on industrial data from a progressive stamping machine. The paper discusses the promising results and potential limitations.
Mathematical Modeling of Thermal Behavior in Layer-by-Layer Part Fabrication by Direct Metal Laser Sintering Process for Different Scanning Patterns
Authors: Sezer Hayri , Ahsan Nazmul , Kozhumal Shijin P. , Ritenour Andy , Kaul Sudhir
Published: January 2021

In direct metal laser sintering process (DMLS), the nonuniform heat transfer and resulting temperature gradient across the part result in thermal residual stress within the part which introduces local deformation. This overall effect ultimately leads to part distortion and affects the mechanical properties of the part. As far as temperature gradient and thermal residual stress are concerned, the crucial process parameter that can be tailored to alleviate the thermal anisotropic effect from the laser heat source is the scanning pattern. In this study, an in-house transient three-dimensional computational model has been developed to analyze thermal behavior in the DMLS process for different scanning patterns. The governing equations for heat transfer are discretized using a finite volume method. An implicit scheme is used for time integration. The thermo-physical properties, thermal conductivity of the metal powder, convection heat transfer coefficient, and specific heat of the metal powder are updated for every time step. The model considers convective and radiative Neumann boundary conditions for the lateral and top surfaces and a constant temperature boundary condition for the bottom surface of rectangular geometries. The laser power is implemented as a moving radiative Neumann boundary condition that follows any given scanning pattern. In this study, two contour parallel (spiral) scanning patterns, center to edge and edge to center, and their corresponding thermal effects have been analyzed. The results show that rectangular spiral pattern with a center to edge scanning direction has the lowest thermal gradient which results in the lowest residual stresses.
Investigation of the Influence of Consequential Design Parameters on the Mechanical Performance of Biodegradable Bone Scaffolds, Fabricated Using Pneumatic Micro-Extrusion Additive Manufacturing Process
Authors: Zhao Daguan , Yu Mohan , Lawrence Logan , Claudio Pier Paolo , Day James B. , Salary Roozbeh (Ross)
Published: January 2021

Pneumatic micro-extrusion (PME) is a high-resolution direct-write additive manufacturing process, which has emerged as the process of choice for tissue engineering and biofabrication of a broad spectrum of organs and tissues (e.g., bone, aortic valve, blood vessels, human ear, and nose). Despite the advantages and host of biomedical applications engendered by the PME process — including, for example, (i) accommodation of a wide range of material viscosity (enabled via thermopneumatic material deposition), (ii) large build volume and standoff distance for tissue engineering, (iii) in situ UV curing, and (iv) high-resolution multimaterial deposition — there are intrinsically complex design, material, and process factors as well as interactions, which influence the functional properties of PME-fabricated tissues and organs. Consequently, investigation of the impact and interaction of each factor aligned with establishment of a physics-based, optimal material deposition regime is inevitably a burgeoning need.

In this study, using the Taguchi design, the influence of four significant factors, i.e., layer height, infill density, infill pattern, and print speed, is investigated on the compression properties as well as the dimensional accuracy of polycaprolactone (PCL) bone scaffolds, fabricated using the PME process. Furthermore, a 3D, transient two-phase flow CFD model is forwarded with the aim to observe the flow of material within the deposition head as well as the micro-capillary (nozzle). The results of this study pave the way for further investigation of the bio-functional properties of bone scaffolds, e.g., biodegradation, cell proliferation and growth rate.
A new species of Adamystis Cunliffe (Acari: Trombidiformes: Adamystidae) from mangrove in the Persian Gulf, Iran, with a key to world species of the genus

Authors: Paktinat-Saeij Saeid , Kazemi Shahrooz
Published: January 2021

Adamystis persiangulfensis sp. nov. is described based on female, male, tritonymph, deutonymph and larva stages collected in the littoral zone of mangrove forests in Qeshm Island, in the eastern part of the Persian Gulf, southern Iran. This new species is distinguished by having two pairs of adoral setae; chelicera with one seta; palpal tarsus with 14 setae; idiosoma with one poorly defined (weakly sclerotized) shield; dorsum laterally at least with 19 pairs of lens-like structures and five pairs of aggenital setae (ag1–5). Additionally, an identification key to known species of Adamystis is updated.
Inhomogeneous and Anisotropic Mechanical Properties of the Triceps Surae Aponeuroses in Older Adults: Relationships With Muscle Strength and Walking Performance
Authors: Shan Xiyao , Evangelidis Pavlos , Yamagishi Takaki , Otsuka Shun , Tanaka Fumiko , Shibata Shigenobu , Kawakami Yasuo
Published: January 2021

This study investigated (a) site- and direction-dependent variations of passive triceps surae aponeurosis stiffness and (b) the relationships between aponeurosis stiffness and muscle strength and walking performance in older individuals. Seventy-nine healthy older adults participated in this study. Shear wave velocities of the triceps surae aponeuroses at different sites and in two orthogonal directions were obtained in a prone position at rest using supersonic shear imaging. The maximal voluntary isometric contraction torque of the plantar flexors and normal (preferred) and fast (fastest possible) walking speeds (5-m distance) were also measured. The shear wave velocities of the adjoining aponeuroses were weakly associated with plantar flexion torque (r = .23–.34), normal (r = .26), and fast walking speed (r = .25). The results show clear spatial variations and anisotropy of the triceps surae aponeuroses stiffness in vivo, and the aponeurosis stiffness was associated with physical ability in older adults.
Why Are Masters Sprinters Slower Than Their Younger Counterparts? Physiological, Biomechanical, and Motor Control Related Implications for Training Program Design
Authors: Pickering Craig , Hicks Dylan , Kiely John
Published: January 2021

Elite sprint performances typically peak during an athlete’s 20s and decline thereafter with age. The mechanisms underpinning this sprint performance decline are often reported to be strength-based in nature with reductions in strength capacities driving increases in ground contact time and decreases in stride lengths and frequency. However, an as-of-yet underexplored aspect of Masters sprint performance is that of age-related degradation in neuromuscular infrastructure, which manifests as a decline in both strength and movement coordination. Here, the authors explore reductions in sprint performance in Masters athletes in a holistic fashion, blending discussion of strength and power changes with neuromuscular alterations along with mechanical and technical age-related alterations. In doing so, the authors provide recommendations to Masters sprinters—and the aging population, in general—as to how best to support sprint ability and general function with age, identifying nutritional interventions that support performance and function and suggesting useful programming strategies and injury-reduction techniques.
Bacteria and Metabolic Potential in Karst Caves Revealed by Intensive Bacterial Cultivation and Genome Assembly
Authors: Zhu Hai-Zhen , Zhang Zhi-Feng , Zhou Nan , Jiang Cheng-Ying , Wang Bao-Jun , Cai Lei , Wang Hong-Mei , Liu Shuang-Jiang
Published: January 2021

Karst caves are oligotrophic environments that are dark and humid and have a relatively stable annual temperature. The diversity of bacteria and their metabolisms are crucial for understanding the biogeochemical cycling in cave ecosystems.
Supplemental Material: Detrital sanidine 40Ar/39Ar dating confirms <2 Ma age of Crooked Ridge paleoriver and subsequent deep denudation of the southwestern Colorado Plateau
Authors: Heizler M.T. , al. et
Published: January 2021

Geochronology data.
Towards individualised contraceptive counselling: clinical and reproductive factors associated with self-reported hormonal contraceptive-induced adverse mood symptoms
Authors: Lundin Cecilia , Wikman Anna , Bixo Marie , Gemzell-Danielsson Kristina , Sundström Poromaa Inger
Published: January 2021

Objective

The study aim was to establish which demographic, clinical, reproductive and psychiatric factors are associated with self-reported hormonal contraceptive (HC)-induced adverse mood symptoms.

Study design

We compiled baseline data from two Swedish studies: one cross-sectional study on combined oral contraceptive (COC)-induced adverse mood symptoms (n=118) and one randomised controlled trial on adverse mood symptoms on COC (n=184). Both included women eligible for COC use, aged over 18 years. All women answered a questionnaire on HC use and associated mood problems. The Mini-International Neuropsychiatric Interview (M.I.N.I.) was used to capture mood and anxiety disorders. Women who acknowledged HC-induced adverse mood symptoms, ongoing or previously (n=145), were compared with women without any such experience (n=157).

Results

Compared with women without self-reported HC-induced adverse mood symptoms, women with these symptoms were younger at HC start (adjusted odds ratio (aOR) 0.83, 95% CI 0.72 to 0.95), had more often undergone induced abortion (OR 3.36, 95% CI 1.57 to 7.23), more often suffered from an ongoing minor depressive disorder (n=12 vs n=0) and had more often experienced any previous mental health problem (aOR 1.90, 95% CI 1.01 to 3.59).

Conclusions

In line with previous research, this study suggests that women with previous or ongoing mental health problems and women who are younger at HC start are more likely to experience HC-induced adverse mood symptoms. Former and current mental health should be addressed at contraceptive counselling, and ongoing mental health disorders should be adequately treated.

Implications

This study adds valuable knowledge for identification of women susceptible to HC-induced adverse mood symptoms. It should facilitate the assessment of whether or not a woman has an increased risk of such symptoms, and thus enable clinicians to adopt a more personalised approach to contraceptive counselling.
Loss of Wip1 aggravates brain injury after ischaemia/reperfusion by overactivating microglia
Authors: Yan Feng , Cheng Xiang , Zhao Ming , Gong Shenghui , Han Ying , Ding Liping , Wu Di , Luo Yumin , Zuo Wei , Zhu Lingling , Fan Ming , Ji Xunming
Published: January 2021

Background and purpose

The inflammatory response mediated by microglia/macrophages is closely related to cerebral ischaemia/reperfusion injury. Wild-type p53-induced protein phosphatase 1 (Wip1), a serine/threonine phosphatase, is expressed in various tissues. A growing number of reports have suggested that Wip1 is a negative regulator of inflammation in peripheral tissue; however, its role in the central nervous system (CNS) remains unclear. This study aimed to clarify whether Wip1 can inhibit CNS inflammation by regulating microglia/macrophage functions after ischaemic injury.

Methods

A model of middle cerebral artery occlusion and reperfusion was established in mice. CNS inflammation was simulated by lipopolysaccharide treatment of primary microglia. Laser speckle imaging was used to monitor regional cerebral blood flow. Behavioural outcomes were assessed with a TreadScan gait analysis system. TTC staining was used to evaluate the infarct volume, and western blotting and immunofluorescence staining were applied to detect the phenotypical transformation of microglia. ELISA was performed to detect the levels of inflammatory factors.

Results

Wip1 expression was increased after ischaemia/reperfusion. Wip1-knockout (KO) mice displayed more severe brain injury than wild-type mice, as indicated by aggravated motor dysfunction, greater brain infarct volumes and higher expression of inflammatory cytokines (interleukin-6 and tumour necrosis factor alpha) in the brain. We also found that Wip1 depletion increased microglial/macrophage activation in both in vitro and in vivo models, which all showed activation of microglia/macrophages. Lentivirus-Ppm1dreversed the injury induced by Wip1-KO.

Conclusions

Our results suggest that Wip1 may inhibit neuroinflammation by inhibiting microglial/macrophage activation after brain ischaemia/reperfusion injury.
Substituting vetch and chicory for rye in a cover crop mixture enhanced nutrient release
Authors: Furey George N. , Smukler Sean M. , Riseman Andrew
Published: January 2021

Increasing the functional diversity of cover crop polycultures has potential to modify nutrient cycling. Aboveground tissue from rye (Secale cereale), vetch (Vicia villosa subsp. dasycarpa), and chicory (Cichorium intybus) was arranged in litterbags, and rates of nutrient supply were measured. A control, monocultures of each species, a biculture of rye:vetch, and a polyculture of rye:vetch:chicory were compared. Increasing functional diversity through reducing the quantity of rye tissue by 30% to include 10% chicory and 20% vetch increased the total amount of nitrogen released by 257%.
Numerical Simulation of Rock Uniaxial Compressive Strength and Deformation Failure Law under Different Size Conditions
Authors: Tian Zhichao , Tang Chunan , Li Hao , Xing Hui , Ning Xiangda
Published: January 2021

Rock engineering occupies an important position in the 21st century. In the face of rock engineering disasters, we are only looking for the essential problems through experiments on rocks, but rock experiments cannot be realized in large numbers, so the article uses numerical simulation software RFPA (Realistic Failure Process Analysis) 2D Basic to simulate rock under different size conditions numerically. In this paper, a rock model with a diameter of 50 mm is used for simulation research. Meanwhile, five calculation models of height‐to‐diameter ratios of 1.0, 1.5, 2.0, 2.5, and 3 are used. Through simulation calculation, we find that the rock model failure is more than complicated when the value of the height‐to‐diameter ratio is exceedingly low (1), but as the height‐to‐diameter ratio increases, the failure mode will become simpler. The stress‐concentrated failure will be in the form of axial failure. When the height‐to‐diameter ratio increases (1.5–2), other damage cracks appear on the basis of axial cleavage failure. As the height‐to‐diameter ratio continues to increase (about 2.5), only shear failure occurs. When the height‐to‐diameter ratio reaches a relatively high level (3), there will be both axial rip and other damage. When the height‐to‐diameter ratio is oversize, there will be both axial rip failure and end damage.
Intelligent Early Warning System for Construction Safety of Excavations Adjacent to Existing Metro Tunnels
Authors: Tian Wei , Meng Jiang , Zhong Xing-Ju , Tan Xiao
Published: January 2021

With the increasing exploitation and utilization of underground spaces, the excavation of deep foundation pits adjacent to existing metro tunnels is becoming increasingly common. These excavations have the potential to cause safety problems for the operation of the nearby metro. Therefore, to prevent metro tunnel accidents from occurring during the construction process and to ensure the safety of lives and property, it is necessary to establish a risk‐based early warning system. During the excavation process, the main methods for preventing accidents in excavations adjacent to existing metro tunnels are manual analyses based on on‐site monitoring data. However, these methods make it difficult to enact effective control measures in a timely manner owing to the lag of information processing. However, the trial application of artificial neural networks (ANNs) and building information modelling (BIM) for engineering projects provides a new method for solving such problems. This study uses a backpropagation neural network to predict the real‐time deformation of the tunnel based on monitoring data from the adjacent construction site. A safety risk assessment model is then established based on the relevant specifications. Through the establishment of an intelligent warning system, the safety risk to the metro tunnel during the construction process can be displayed in a three‐dimensional (3D) form using the BIM. The operation results of the ANN–BIM system show that it can effectively present the safety risk to existing metro tunnels in a 3D manner, which can provide managers with rapid and convenient visual information to inform their decision‐making.
A Risk Score Model Based on Nine Differentially Methylated mRNAs for Predicting Prognosis of Patients with Clear Cell Renal Cell Carcinoma
Authors: Zhou Jingmin , Liu Guanghua , Wu Xingcheng , Zhou Zhien , Li Jialin , Ji Zhigang
Published: January 2021

Purpose. DNA methylation alterations play important roles in initiation and progression of clear cell renal cell carcinoma (ccRCC). In this study, we attempted to identify differentially methylated mRNA signatures with prognostic value for ccRCC. Methods. The mRNA methylation and expression profiling data of 306 ccRCC tumors were downloaded from The Cancer Genome Atlas (TCGA) to screen differentially methylated lncRNAs and mRNAs (DMLs and DMMs) between bad and good prognosis patients. Uni- and multivariable Cox regression analyses and LASSO Cox-PH regression analysis were used to select prognostic lncRNAs and mRNAs. Corresponding risk scores were calculated and compared for predictive performance in the training set using Kaplan-Meier OS and ROC curve analyses. The optimal risk score was then identified and validated in the validation set. Function enrichment analysis was conducted. Results. This study screened 461 DMMs and 63 DMLs between good prognosis and bad prognosis patients, and furthermore, nine mRNAs and six lncRNAs were identified as potential prognostic molecules. Compared to nine-mRNA status risk score model, six-lncRNA methylation risk score model, and six-lncRNA status risk score model, the nine-mRNA methylation risk score model showed superiority for prognosis stratification of ccRCC patients in the training set. The prognostic ability of the nine-mRNA methylation risk score model was validated in the validation set. The nine prognostic mRNAs were functionally associated with neuroactive ligand receptor interaction and inflammation-related pathways. Conclusion. The nine-mRNA methylation signature (DMRTA2, DRGX, FAM167A, FGGY, FOXI2, KRTAP2-1, TCTEX1D1, TTBK1, and UBE2QL1) may be a useful prognostic biomarker and tool for ccRCC patients. The present results would be helpful to elucidate the possible pathogenesis of ccRCC.
Phase I Study of the CD47 Blocker TTI-621 in Patients with Relapsed or Refractory Hematologic Malignancies
Authors: Ansell Stephen M. , Maris Michael B. , Lesokhin Alexander M. , Chen Robert W. , Flinn Ian W. , Sawas Ahmed , Minden Mark D. , Villa Diego , Percival Mary-Elizabeth M. , Advani Anjali S. , Foran James M. , Horwitz Steven M. , Mei Matthew G. , Zain Jasmine , Savage Kerry J. , Querfeld Christiane , Akilov Oleg E. , Johnson Lisa D.S. , Catalano Tina , Petrova Penka S. , Uger Robert A. , Sievers Eric L. , Milea Anca , Roberge Kathleen , Shou Yaping , O'Connor Owen A.
Published: January 2021

Purpose:

TTI-621 (SIRPα-IgG1 Fc) is a novel checkpoint inhibitor that activates antitumor activity by blocking the CD47 “don't eat me” signal. This first-in-human phase I study (NCT02663518) evaluated the safety and activity of TTI-621 in relapsed/refractory (R/R) hematologic malignancies.

Patients and Methods:

Patients with R/R lymphoma received escalating weekly intravenous TTI-621 to determine the maximum tolerated dose (MTD). During expansion, patients with various malignancies received weekly single-agent TTI-621 at the MTD; TTI-621 was combined with rituximab in patients with B-cell non-Hodgkin lymphoma (B-NHL) or with nivolumab in patients with Hodgkin lymphoma. The primary endpoint was the incidence/severity of adverse events (AEs). Secondary endpoint included overall response rate (ORR).

Results:

Overall, 164 patients received TTI-621: 18 in escalation and 146 in expansion (rituximab combination, n = 35 and nivolumab combination, n = 4). On the basis of transient grade 4 thrombocytopenia, the MTD was determined as 0.2 mg/kg; 0.1 mg/kg was evaluated in combination cohorts. AEs included infusion-related reactions, thrombocytopenia, chills, and fatigue. Thrombocytopenia (20%, grade ≥3) was reversible between doses and not associated with bleeding. Transient thrombocytopenia that determined the initial MTD may not have been dose limiting. The ORR for all patients was 13%. The ORR was 29% (2/7) for diffuse large B-cell lymphoma (DLBCL) and 25% (8/32) for T-cell NHL (T-NHL) with TTI-621 monotherapy and was 21% (5/24) for DLBCL with TTI-621 plus rituximab. Further dose optimization is ongoing.

Conclusions:

TTI-621 was well-tolerated and demonstrated activity as monotherapy in patients with R/R B-NHL and T-NHL and combined with rituximab in patients with R/R B-NHL.
Personalized Preoperative Education Reduces Perioperative Anxiety in Old Men with Benign Prostatic Hyperplasia: A Retrospective Cohort Study
Authors: Li Lihong , Li Shasha , Sun Yating , Zhang Shaoxia , Zhang Xue , Qu Haiming
Published: January 2021

Introduction: Psychological health is important to old patients with benign prostatic hyperplasia (BPH) after prostatic surgery. In this retrospective cohort study, we evaluated the effect of personalized preoperative education in the reduction of perioperative anxiety in old BPH patients after prostatic surgery. Methods: Senior patients (≥65 years) admitted with a diagnosis of BPH and scheduled for initial transurethral resection of the prostate from January 1, 2017 to November 30, 2019 were retrieved. Patients in the preoperatively educated group completed the Chinese version of generalized anxiety disorder 7-item scale (GAD-7) form to evaluate their anxiety level at admission and 14 days clinical visits after individual preoperative education. Patients in the control group completed GAD-7 forms but did not receive personalized preoperative education. Patients in both groups discussed their disease with physicians during clinic visits and after admission, and were given an informed consent about their treatment plans. Results: Seven hundred and twenty-four patients were retrieved, including 312 patients who received preoperative education and 412 patients who did not. There were significantly lower postoperative GAD-7 score and fewer moderate to severe postoperative anxiety patients in the preoperatively educated group (p < 0.01). Patients with education above secondary education level had less perioperative anxiety. Conclusion: Personalized education incorporated with shared valuable physiological and psychological experience and expectations dealing with BPH, in comparison to traditional uniformed patient education and informed consent before surgery, may reduce perioperative anxiety more efficiently in BPH patients. A higher educational level helps patients reduce perioperative anxiety before and after their personalized preoperative education.
Week 2 Symptomatic Response with Vedolizumab as a Predictive Factor in Japanese Anti-TNFα-Naive Patients with Ulcerative Colitis: A post hoc Analysis of a Randomized, Placebo-Controlled Phase 3 Trial
Authors: Nagahori Masakazu , Watanabe Kenji , Motoya Satoshi , Ogata Haruhiko , Kanai Takanori , Matsui Toshiyuki , Suzuki Yasuo , Pinton Philippe , Ursos Lyann , Sakamoto Shigeru , Shikamura Mitsuhiro , Hori Tetsuharu , Fernandez Jovelle , Hibi Toshifumi , Watanabe Mamoru
Published: January 2021

Background and Aim: To evaluate the onset of symptomatic response with vedolizumab in patients with moderate-to-severe ulcerative colitis in Japan. Methods: Patients were randomized to receive vedolizumab 300 mg or placebo at Weeks 0, 2, and 6. Mayo subscores were analyzed in patients with baseline stool frequency (SF) ≥1 and rectal bleeding (RB) ≥1. In patients with baseline SF ≥2 and RB ≥1, the proportion who achieved SF ≤1 and RB = 0 was determined. Results: Patients were randomized to vedolizumab (n = 164) or placebo (n = 82). Decrease from baseline in mean SF subscore was greater with vedolizumab versus placebo from Week 2 (−6.6%; 95% confidence interval [CI], −16.2, 3.0), with a greater difference in anti-tumor necrosis factor (TNF)α-naive patients (vedolizumab vs. placebo, −13.2%; 95% CI, −29.7, 3.3). Mean percentage decrease from baseline RB subscore was numerically greater with vedolizumab versus placebo from Week 6 in anti-TNFα-naive patients (−10.7%; 95% CI, −33.0, 11.5). More patients in the anti-TNFα-naive subgroup achieved SF ≤1 and RB = 0 with vedolizumab versus placebo at Week 2 (14.8%; 95% CI, 2.5, 27.0) and Week 6 (20.3%; 95% CI, 4.4, 36.2). Patients with SF ≤1 and RB = 0 at Week 2 had higher clinical response, clinical remission, and mucosal healing rates at Week 10 than those without. Conclusions: Our results indicate that vedolizumab induces a rapid symptomatic response, particularly in anti-TNFα-naive patients, and suggest that early symptomatic improvement predicts treatment response at Week 10 (NCT02039505).
Dynamic Tests in Pituitary Endocrinology: Pitfalls in Interpretation during Aging
Authors: Caputo Marina , Mele Chiara , Ferrero Alice , Leone Ilaria , Daffara Tommaso , Marzullo Paolo , Prodam Flavia , Aimaretti Gianluca
Published: January 2021

Aging and age-related diseases represent hot topics of current research. Progressive damage in morphology and function of cells and tissue characterizes the normal process of aging that is influenced by both genetic and environmental factors. The ability of each individual to adapt to these stressors defines the type of aging and the onset of age-related diseases (i.e., metabolic syndrome, inflammatory disorders, cancer, and neurodegenerative diseases). The endocrine system plays a critical role in this process because of its complex relationships with brain, immune system, and skeletal muscle; thus, alterations in hormonal networks occur during aging to maintain homeostasis, with consequent under- or overactivity of specific hypothalamic-pituitary-peripheral hormone axes. On the other hand, the increase in life expectancy has led to increasing incidence of age-related diseases, including endocrine disorders, which may prompt assessment of endocrine function in aging individuals. In this context, there is growing awareness that natural changes of endocrine physiology and physiopathology occurring with increasing age may necessitate age-driven diagnostic cutoffs requiring validation in the elderly. This review aims to analyze the available literature on the hormone response to the most important dynamic tests currently used in the clinical practice for the screening of anterior pituitary-related diseases to underline pitfalls in interpretation during aging.