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Bearing plays an important role in industrial equipment and it may operate under varying conditions. When the speed of shaft changes, whether monotonous or non-monotonous speed, common diagnostic approaches cannot effectively extract fault features. But encoders and tachometers are not always available. Therefore, tacholess order tracking methods which can directly extract the instantaneous rotating frequency (IRF) from vibration signal are very useful in bearing fault diagnosis under varying speed. Among these methods, the generalized linear chirplet transform (GLCT) can produce time-frequency representation without constructing any mathematical model, but there are two parameters must be set in advance. The parameters have great influence on the analysis result. To reduce the dependence on the prior knowledge of presetting the parameters in varying conditions, two different improved GLCT methods are proposed in this paper. To do with the situation where the trend of speed changes is monotonous, the scale-space is introduced to lift GLCT which can adaptively set a vital parameter, and the other parameter is set to default value. When faced with non-monotonous speed, the second method is proposed which the grey wolf optimizer (GWO) and Gini index are introduced to search the optimal parameters of GLCT without any prior knowledge. With the help of the proposed methods, the IRF can be extracted directly from vibration signal. Then, the raw signal can be resampled based on the IRF to eliminate the influences of speed. The morphological filtering is adopted to remove the noise and extract the fault characteristics order (FCO). Another two typical time-frequency analysis methods are used for comparisons. Three different signals are used for analysis to demonstrate the superiority of the proposed methods.

Image annotation aims to jointly predict multiple tags for an image. Although significant progress has been achieved, existing approaches usually overlook aligning specific labels and their corresponding regions due to the weak supervised information (i.e., ``bag of labels'' for regions), thus failing to explicitly exploit the discrimination from different classes. In this article, we propose the deep label-specific feature (Deep-LIFT) learning model to build the explicit and exact correspondence between the label and the local visual region, which improves the effectiveness of feature learning and enhances the interpretability of the model itself. Deep-LIFT extracts features for each label by aligning each label and its region. Specifically, Deep-LIFTs are achieved through learning multiple correlation maps between image convolutional features and label embeddings. Moreover, we construct two variant graph convolutional networks (GCNs) to further capture the interdependency among labels. Empirical studies on benchmark datasets validate that the proposed model achieves superior performance on multilabel classification over other existing state-of-the-art methods.

In this study, we propose an efficient optimization algorithm that is a hybrid of the iterated greedy and simulated annealing algorithms (hereinafter, referred to as IGSA) to solve the flexible job shop scheduling problem with crane transportation processes (CFJSP). Two objectives are simultaneously considered, namely, the minimization of the maximum completion time and the energy consumptions during machine processing and crane transportation. Different from the methods in the literature, crane lift operations have been investigated for the first time to consider the processing time and energy consumptions involved during the crane lift process. The IGSA algorithm is then developed to solve the CFJSPs considered. In the proposed IGSA algorithm, first, each solution is represented by a 2-D vector, where one vector represents the scheduling sequence and the other vector shows the assignment of machines. Subsequently, an improved construction heuristic considering the problem features is proposed, which can decrease the number of replicated insertion positions for the destruction operations. Furthermore, to balance the exploration abilities and time complexity of the proposed algorithm, a problem-specific exploration heuristic is developed. Finally, a set of randomly generated instances based on realistic industrial processes is tested. Through comprehensive computational comparisons and statistical analyses, the highly effective performance of the proposed algorithm is favorably compared against several efficient algorithms.

This paper considers the problem of scheduling automated guided vehicles (AGVs) with battery constraints. Each transport request involves a soft time window, and the AGV fleet used to service those requests is heterogeneous with a diverse set of capabilities and travel costs. In contrast to the existing literature, each transport request may require different AGV material handling capabilities (such as lift loads, tow loads, or handle loads with a mounted robot arm), and the AGV batteries can be recharged partially under consideration of a critical battery threshold. The problem is to assign the transport and charging requests to AGVs, sequence the requests, and determine their starting times and the recharging durations of the AGVs with the objective of minimizing a weighted sum of the tardiness costs of transport requests and travel costs of AGVs. A mixed-integer linear programming model is formulated. We also propose a new matheuristic that makes use of an adaptive large neighborhood search algorithm and a linear program to solve industry-size instances. We illustrate the efficacy of our approach with an industry case study using real-world data.

Passive shoulder supports show large potential for a wide range of applications, such as assisting activities of daily living and supporting work-related tasks. The rigid-link architecture used in currently available devices, however, may pose an obstacle to finding designs that offer low protrusion and close-to-body alignment. This study explores the use of mechanisms that employ a flexible element which connects the supported arm to an attachment at the back and acts as energy storage, transmission and part of the load bearing structure. Based on the synthesis method explained in this paper, a large scope investigation into possible flexure-based mechanism topologies is conducted. Thereby, many potential designs are discovered, which are presented, categorized and compared. Two promising designs are developed into prototypes, and are built and tested on a dedicated test bench. These two mechanisms reduce the necessary moment to lift the arm by more than 80 % throughout 85 % of the range of motion, while staying within 18 cm and 10 cm distance from the body, respectively. The study indicates that, due to its lower protrusion and interface loads, a design with a tapered flexure connecting the upper arm via a hinge to a spring-loaded slider at the back offers the most promising solution.

This article proposes new improvements to the ECMS-based control of plug-in hybrid electric vehicles (PHEVs) using macro-level trip forecast information. First, the dynamic programming (DP) optimization is applied to a power-split PHEV model to obtain the optimal powertrain trajectories for benchmarking the energy economy of the proposed controllers. An instantaneous energy cost minimization process is then formulated to compute the optimal mix of fuel and electricity, subject to the state and input constraints. To improve the speed and accuracy of the energy management system, the Nelder-Mead simplex search algorithm is used for the instantaneous optimizations. To account for the battery capacity limitation, an adaptive electricity pricing policy is introduced to control battery discharge rate based on the remaining trip distance, average speed, and elevation forecasts. The parameters of the proposed policy are optimized for a group of 5 urban and highway drive cycles to obtain a robust controller which can serve a wide spectrum of driving patterns. To further improve the energy economy, an extended-horizon optimization algorithm is proposed to account for control input transitions between consecutive time steps. Finally, a revised speed forecast formula is implemented during the low-SOC intervals to lift battery SOC ahead of high-demand periods. The combination of the proposed schemes enables reaching over 99% average optimality compared to a finely discretized DP optimization for the adopted drive cycles, and above 98% optimality for a test PHEV drive cycle.

This paper presents an approach to reframe the sizing problem for vertical-lift unmanned aerial vehicles (UAVs) as an optimization problem and obtains a weight-optimal solution with up to two orders of magnitude of savings in wall clock time. Because sizing is performed with higher fidelity models and design variables from several disciplines, the Simultaneous Analysis aNd Design (SAND) approach from fixed-wing multidisciplinary optimization literature is adapted for the UAV sizing task. Governing equations and disciplinary design variables that are usually self-contained within disciplines (airframe tube sizes, trim variables, and trim equations) are migrated to the sizing optimizer and added as design variables and (in)equality constraints. For sizing consistency, the iterative weight convergence loop is replaced by a coupling variable and associated equality consistency constraint for the sizing optimizer. Cruise airspeed is also added as a design variable and driven by the sizing optimizer. The methodology is demonstrated for sizing a package delivery vehicle (a lift-augment quadrotor biplane tailsitter) with up to 39 design variables and 201 constraints. Gradient-based optimizations were initiated from different starting points; without blade shape design in sizing, all processes converged to the same minimum, indicating that the design space is convex for the chosen bounds, constraints, and objective function. Several optimization schemes were investigated by moving combinations of relevant disciplines (airframe sizing with finite element analysis, vehicle trim, and blade aerodynamic shape design) to the sizing optimizer. The biggest advantage of the SAND strategy is its scope for parallelization, and the inherent ability to drive the design away from regions where disciplinary analyses (e. g., trim) cannot find a solution, obviating the need for ad hoc penalty functions. Even in serial mode, the SAND optimization strategy yields results in the shortest wall clock time compared to all other approaches.

The Wagner function represents the response in lift on an airfoil that is subject to a sudden change in conditions. While it plays a fundamental role in the development and application of unsteady ...

BACKGROUND: One of the most popular short-scar rhytidectomy techniques used nowadays is the minimal access cranial suspension (MACS) lift developed by Tonnard and Vaerpele. The technique uses purse-string sutures in combination with limited skin undermining to obtain a clear vertical tissue repositioning. Since its introduction, the technique has extensively been described and used around the world by facial plastic surgeons. Now, 18 years after its introduction, a systematic review concerning the results and complications of the MACS lift is presented to establish its current position in facial rejuvenation. METHODS: The MEDLINE, Embase, Cochrane Central, and Google Scholar databases were searched for studies evaluating the MACS lift (June 10, 2020). Outcomes of interest were long-term effect, satisfaction, and complications of the MACS lifting as determined by the patient and/or surgeon. RESULTS: Six studies were included, with 739 patients treated with the MACS lift in total. No major complications were reported, four studies did report on the occurrence of minor complications. All of the six studies reported relatively high levels of satisfaction. Three studies reported a shorter procedural duration for the MACS lift compared with the conventional facelift. In three of the six included studies, the level of evidence was low. The effect on neck rejuvenation is limited. CONCLUSION: The MACS lift can be considered a minimally invasive facelift procedure with a relatively low complication rate. The procedure, often combined with additional procedures, results in evident patient and/or surgeon satisfaction. To obtain a better desired result on an aged neck area, additional procedures are warranted.

Origami structures can transform their form and function by changing the direction of their folds. This reconfiguration can enable multifunctional robots, but doing so requires a fast, robust, and repeatable actuation method. In this article, we present an origami gripper that uses dynamic transformation to change its kinematic behavior in less than a second. We characterize individual vertices to show that the transformation is predictable and repeatable for different designs and orientations. We then apply it to a multivertex template that is capable of a wide range of shapes and motion patterns, indicating that transformation can be generalized to complex and functional machines. To demonstrate this, we built a transforming origami gripper on a robotic arm to pick up multiple objects. Demonstrations show that the gripper can quickly reconfigure between three different grasping modes and has sufficient stiffness to engage with and lift multiple objects with distinct geometries.

In this work, we advance the security promise of split manufacturing through judicious handling of interconnects. First, we study the cost-security trade-offs underlying for split manufacturing, which are limiting its adoption. Next, aiming to resolve these concerns, we propose three effective and efficient strategies to dedicatedly lift nets to higher metal layers. Towards this end, we design custom “elevating cells” and devise procedures for routing blockages. All our techniques are employed in a commercial-grade computer-aided design (CAD) framework. For our security analysis, we leverage various state-of-the-art attacks (network flow-based attack, routing-congestion-aware attack, and deep learning-based attack), established metrics (CCR, OER, and HD), and advanced metrics (percentage of netlist recovery and mutual information). Our extensive experiments show that our scheme provides superior protection. Simultaneously, we induce reasonably low and controllable overheads on power and performance, without any silicon area costs. Besides, we support higher split layers, which helps to alleviate concerns on the practicality of split manufacturing.

A synthetic air data system (SADS) is an analytical redundancy technique that is crucial for unmanned aerial vehicles (UAVs) and is used as a backup system during air data sensor failures. Unfortunately, the existing state-of-the-art approaches for SADS require GPS signals or high-fidelity dynamic UAV models. To address this problem, a novel synthetic airspeed estimation method that leverages deep learning and an unscented Kalman filter (UKF) for analytical redundancy is proposed. Our novel fusion-based method only requires an inertial measurement unit (IMU), elevator control input, and airflow angles while GPS, lift/drag coefficients, and complex aircraft dynamic models are not required. Additionally, we demonstrate that our proposed temporal convolutional network (TCN) is a more efficient model for airspeed estimation than the renowned models, such as ResNet or bidirectional long short-term memory (LSTM). Our deep learning-aided UKF was experimentally verified on long-duration real flight data and has promising performance compared with the state-of-the-art methods. In particular, it is confirmed that our proposed method robustly estimates the airspeed even under dynamic flight conditions where the performance of conventional methods is degraded.

We can estimate the size of a speaker solely from their speech sounds, regardless of whether the sounds are voiced or unvoiced. In this study, we developed a size perception model based on the computational theory of the stabilised wavelet transform (SWT) to explain a variety of size discrimination data. We also conducted extended experiments to evaluate the effect of spectral lift on speaker size discrimination, from voiced and unvoiced speech sounds. The just noticeable difference (JND) and the point of subjective equality (PSE) for speaker size discrimination were compared between speech sounds with natural and lifted spectra. On average, listeners tended to judge that the lifted speech came from a smaller speaker. The PSE, which indicates the systematic difference in perceived size, shifted by approximately 10% (Exp. 1) for unvoiced speech sounds, and by approximately 5% (Exp. 2) for voiced speech sounds. The JND depended on the spectral lift for unvoiced sounds, but not with voiced sounds. At the same time, it was noted that there were large differences between listeners: some listeners’ judgements were affected by the spectral lift, while others were not. We constructed a size discrimination model to explain all of the experimental results with listener dependence for voiced and unvoiced speech sounds. We introduced a weighting function, based on the Size-Shape Image (SSI) in the SWT, which reduces the influence of resolved harmonics caused by the glottal pulse sequence in voiced speech. As a result, the model with the SSI weighting function predicted fairly well the individual listener’s data, whether the judgements were affected by the spectral lift or not, and whether the speech sounds were voiced or unvoiced. The optimum choice of one parameter, that is, the spectral compensation coefficient, enabled us to explain the data of all individuals.

At present, container handling facilities are huge in size, low in automation, and complicated to operate, which are not suitable for applications in the limited spaces. Inspired by humans’ flexible collaboration when carrying a heavy and large object, in this article we devise a novel dual-forklift collaborative mechanism to address this problem. Specifically, we design a turn lock and hydraulic lifting structure to enable a rigid connection between each forklift and the target container, deploy a four-wheel steering structure in each forklift for omnidirectional motion, and construct a novel vision system by leveraging both RGB camera and time-of-flight depth camera. Furthermore, to provide visual feedback to the controller such that the dual forklift can connect, lift, and handle the container successfully, we devise a coarse-to-fine container detection and corner junction location model. Experiments demonstrate that our model outperforms representative models in terms of both precision and efficiency. Besides, the designed dual-forklift system can accomplish the handling tasks at narrow spaces, confirming its practical value in industrial applications.

Dr. Michael Reinhorn performs a pilonidal cleft lift procedure, thoroughly describing the pre-op, post-op, and intraoperative steps, on a young man who pre

Purpose Aircraft maintenance technician (AMT) is the most critical profession in the aircraft maintenance system. The tasks of a licensed AMT require expertise and involve repetitive physical tasks such as tightening or loosening aircraft parts, carrying or removing parts during long working hours under time pressure and day/night shifts. This study aims to attract attention to the difficult working conditions of AMTs and identify the body parts that are at risk of musculoskeletal disorder (MSD). Design/methodology/approach A questionnaire is developed by the authors to gather demographic information, use of hand tools, equipment, use of fall protection, manual material handling (lifting, pushing, pulling), load weight, environmental factors, and MSD discomfort level perceptions. The questionnaire is applied to 150 AMTs during six months period, and the obtained data are analyzed by sequential ordinal logistic regression (OLR) models. Findings The ORL results confirm that the use of equipment (lift platform, scissors lift), safety belt attached to the platform, manual material handling, environmental factors (humidity, vibration and illumination) and resting periods have a significant effect on MSD risks. On the contrary, age, experience level, use of small hand tools, temperature and noise are not identified as statistically significant. Originality/value The study is original for it considers the working conditions and perceived discomfort levels of AMTs. A questionnaire is introduced to assess the consequences of the use of tools, equipment, fall protection equipment, environmental conditions and work organization on various body parts (neck, shoulder, elbow, back, lower back, wrist-hand, hip, knee, and ankle-feet), and strain level is identified. The study contributes to the theoretical aircraft maintenance literature and managers in practice.

In Bangladesh, groundwater is the main source of both drinking water and irrigation. Suction lift pumps and force mode of operation are the predominant technologies for groundwater abstraction in Bangladesh. For a sustainable usage policy, it is thus important to identify which technology would be more appropriate for which area in Bangladesh. With that aim in mind, this paper proposes a methodology that leverages the power of machine learning that can potentially learn intricate relationships between the (annual maximum) groundwater level (GWL) and the relevant hydrogeological factors (HGFs). A number of machine learning algorithms—both classification and regression models—was trained. Our classification models were trained as a binary classifier to predict the abstraction technology of a particular point. Notably, our best classification model was based on the Random Forest algorithm, which achieved an accuracy of 91% and an excellent value of 96% for the area under receiver operating characteristics curve, indicating its strong discriminant capability. We also identified (elevation derived from) digital elevation model, specific yield and lithology as the three most important HGFs for GWL in Bangladesh. On the other hand, to predict the actual (annual maximum) GWL, we employed a two-stage approach, where we first employed the above-mentioned classification model to identify the suitable abstraction technology for the point of interest and subsequently predict the actual GWL using the appropriate Random Forest regressor. This also had a reasonable accuracy (minimum absolute error was less than 1 for suction mode and less than 5 for the force mode). Finally, using our prediction models, we prepared groundwater (technology) maps for the whole Bangladesh.

The “BENIN TERMINAL” machines are maintained by company technicians who encounter difficulties in the operations carried out on these machines. In fact, it is about improving the procedure for installing and removing engines and gearboxes for BENIN TERMINAL mobile vehicles through the study and design of a single scissor lift table. It has a lifting capacity of 2 tons, a width of 900 mm, a total length of 1900 mm and a maximum height of 2000 mm using a hydraulic system. It works with 12 V batteries, simple and height-adjustable workspace. The lifting table also allows certain operations requiring an average height to be carried out.This device was developed for the BENIN TERMINAL garage in order to reduce the efforts and risks encountered by technicians when installing or removing engines and gearboxes on certain machines, in particular heavy machines such as Reach Stackers and 16ton forklifts.

Viewing one’s smartphone whilst walking commonly leads to a slowing of walking. Slowing walking speed may occur because of the visual constraints related to reading the hand-held phone whilst in motion. We determine how walking-induced phone motion affects the ability to read on-screen information. Phone-reading performance (PRP) was assessed whilst participants walked on a treadmill at various speeds (Slow, Customary, Fast). The fastest speed was repeated, wearing an elbow brace (Braced) or with the phone mounted stationary (Fixed). An audible cue (‘text-alert’) indicated participants had 2 s to lift/view the phone and read aloud a series of digits. PRP was the number of digits read correctly. Each condition was repeated 5 times. 3D-motion analyses determined phone motion relative to the head, from which the variability in acceleration in viewing distance, and in the point of gaze in space in the up-down and right-left directions were assessed. A main effect of condition indicated PRP decreased with walking speed; particularly so for the Braced and Fixed conditions (p = 0.022). Walking condition also affected the phone’s relative motion (p p ≤ 0.05). There was an inverse association between phone acceleration variability and PRP (p = 0.02). These findings may explain why walking speed slows when viewing a hand-held phone: at slower speeds, head motion is smoother/more regular, enabling the motion of the phone to be coupled with head motion, thus making fewer demands on the oculomotor system. Good coupling ensures that the retinal image is stable enough to allow legibility of the information presented on the screen.

PurposeBlockchain and distributed ledger technologies are set to disrupt the real estate sector in all areas: ownership, sale, management and investment. Tokenization moves physical real estate to the digital space and could result in substantial cost savings in the pre- and post-tokenization process. This article discusses whether real estate as an asset class is ready for digitalization in the Asia-Pacific (APAC) region.Design/methodology/approachGlobally, the APAC region has the highest digital adaptation/adoption rates. Regulators in the region are also moving fast to clarify their stance on digital assets. This article adopts a holistic view, from trends, regulations, and technology, to discuss the benefits and challenges of digitalizing real estate in APAC.FindingsReal estate tokenization is a nascent market but platforms like BrickX, KASA, ADDX, and Minterest have successfully launched real estate tokens in Australia, South Korea, and Singapore, respectively. Tokenization may prove to be a viable funding source for those relatively poorly capitalized financial markets in the APAC region.Practical implicationsThis paper discusses the current regulatory and business contexts in relation to the pace of tokenization of real estate in APAC. Opportunities and difficulties are outlined in a concise manner to facilitate more discussion in this area.Originality/valueExisting reports and research articles tend to focus on the western markets. This article provides a new perspective on tokenization, specifically in the APAC context.

This paper addresses the analysis of the design, manufacture, and assembly (DFMA) of the tray for a vertical lift module (Tray VLM), being a subassembly of this automatic VLM storage system. The method used for DFMA analysis is the Boothroyd Dewhurst method, using their software. Based on the recommendations of the DFMA software, following the study on the current Tray VLM product, several components were redesigned using the Design for Manufacture (DFM) module and certain stages for assembly were optimized, using the design for Assembly module (DFA). The result was reduced assembly cost, reduced assembly process time, and increased assembly design efficiency, which were successfully validated by DFMA software by maximizing the DFA index

Supplemental Digital Content is available in the text., Background: The composite face lift is becoming increasingly popular following recent advances in understanding of facial anatomy that enable safe sub-superficial musculoaponeurotic system (SMAS) dissection. This article presents the authors’ technique for composite face lift in Asian patients and reviews their experience and outcome with this procedure. Methods: Composite face lifts were performed on 128 Asian patients between January of 2010 and June of 2020. Ninety-four were primary face lifts, and 34 were secondary or tertiary face lifts. The authors’ surgical technique and adaptations for the specific requirements of Asian patients are described in detail. The mean follow-up was 26 months (range, 6 to 108 months). Fat grafting was an integral part of our procedure, with 95 percent having concomitant facial fat grafting with their face lift. Results: Patients were followed up in accordance with a standardized schedule. The majority of patients reported high satisfaction with the aesthetic outcome of the technique, with natural, long-lasting results. The face lift plane of dissection is through the facial soft-tissue spaces, which provide atraumatic sub-SMAS access with precise release of the intervening retaining ligaments for effective flap mobilization. By emphasizing tension on the composite flap with no tension on the skin closure, the scars were discrete in the great majority of patients. Complications were few, with no hematomas or skin flap necrosis. The temporary nerve injury rate was 1.5 percent, with no patient having a permanent nerve injury. Conclusion: The composite face lift is an ideal technique for Asian patients, as it delivers natural, long-lasting results; a quick recovery; and high patient satisfaction. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, IV.

Background Body-contouring is a surgical field in growing demand, as the number of massive weight loss patients following bariatric surgery is increasing. The purpose of this study was to provide a straightforward and time-efficient circumferential body lift technique to achieve optimal lower truncal contouring. Patients and methods A total of 155 massive weight loss patients (133 women and 22 men) underwent lower body lift surgery between 2006 and 2018. The mean preoperative weight reduction and body mass indices were 56.5 ± 16.6 kg and 26.7 ± 4.7 kg/m2, respectively. The preoperative markings focused on the back and gluteal region, and the modified surgical technique are described. Additionally, improvements of intra-operative repositioning of the patient and how to deal with sterilization and dressings are elucidated. Results The average intra-operative time was 178 ± 54.6 minutes. The mean follow-up of all patients was 8.2 ± 2.4 years. The most common complications were related to wound dehiscence (n = 38) and seroma (n = 18). The mean weight of the resected tissue was 3 056 ± 1 816.5 g. Conclusion The lower body lift represents an effective and safe body contouring procedure to treat massive weight loss patients with multiple regions of concern. The current study describes a modified surgical technique that reduces operating time and complications, notably. Level of evidence iv This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors http://www.springer.com/00266 .

To achieve the three-dimensional free movement of the slung load, a load-leading hierarchical control strategy has been adopted recently which divides the cooperative multi-lift system into a load layer, a cable layer, and an aircraft layer. But there exists a non-convex optimization problem in the cable layer when computing the force of each cable, and more control difficulties of the aircraft due to the additional disturbances resulting from the load movement. To solve these problems, an application of the social spider optimization (SSO) algorithm and the improved active disturbance rejection controller (IADRC) in hierarchical control of cooperative multi-lift with four unmanned helicopters is proposed in this study. First, the unmanned helicopters as well as the load are modeled. Then the three layers mentioned above are designed, respectively. Specifically, an optimization method combining SSO with the MATLAB/fmincon function is proposed to solve the non-convex problem in the cable layer. And within the unmanned helicopter layer, the fuzzy theory is introduced into the nonlinear error feedback control strategy of the traditional active disturbance rejection controller (ADRC) to realize the control of the unmanned helicopter. At last, some simulations are carried out, and the results indicate that the system has higher calculation efficiency, smaller steady-state error, and better adaptability to trajectory change or load release with the designed hierarchical control strategy.

Current trends in microelectronics chip bonding and assembly encompass ultra-fine pitch components with flexible form factors and advanced die-attach materials, which can sustain conformal strain without compromise in adhesion and reliability. These trends have highlighted the need for advanced microfrabrication technologies, which allow the on-demand digital fabrication of interconnections and die-attach bumps on chip carriers and interposers with challenging topographies. Laser printing, based on the laser induced forward transfer (LIFT) technique, has addressed such micromanufacturing challenges over the past decade. Several previous demonstrations of highly resolved and conformal interconnections for the bonding and packaging of micro and opto-electronic components are summarized in this paper. Latest advances in the laser printing and laser sintering of highly viscous nanopastes for achieving planar or three-dimensional (3D) structures consisting of Ag paste are demonstrated. The latter is achieved by stacking of arrays or bumps in a digital manner. The reported results verify that LIFT offers control over both the lateral and vertical dimensions. This control can facilitate the soldering process of heterogeneous components, whose pads have significant height and pitch dissimilarities. The applicability of LIFT in the fields of packaging and assembly of flexible and heterogeneous integration schemes, is further validated.

Employing an ejector to recover the expansion work of the auto-cascade refrigeration cycle is a feasible method to improve the system performance. The system operation characteristics are closely relevant to the ejector geometry parameters. In order to obtain the critical structure parameters influencing the freezer's pull-down performance, experimental research was conducted on an ejector-enhanced auto-cascade refrigeration cycle applied in a low-temperature freezer. The impacts of the ejector nozzle throat, mixing chamber diameter and length, and the nozzle exit position on the system's pull-down and steady operation characteristics were explored. The experimental results illustrated that the cooling rate and the attainable freezing temperature were mainly influenced by the nozzle throat and mixing chamber length instead of the nozzle exit position and mixing chamber diameter. The nozzle throat diameter of 0.52 mm and the mixing chamber length of 25 mm was optimal concerning the fastest cool-down rate and lowest freezing temperature of -61.2 °C. At the early phase of the pull-down process, a small mixing chamber diameter would cause the ejector malfunction of the pressure lift. There was a worst nozzle exit position of slowing down the pull-down speed, rising the freezing temperature, and reducing the system COP and exergy efficiency at the given operations. The ejector yielded the maximum pressure lift ratio of 1.196 and the entrainment ratio of 0.523 at the optimal ejector geometries. This work would be helpful to guide the ejector structure optimization for the ejector-enhanced auto-cascade low-temperature freezers.

This paper introduces a linearized model of electrocaloric cooling. The model is derived for electrocaloric Brayton, Carnot, and Otto cycles, and a more practical hybrid constant voltage-charge (HCVC) variation of the Otto cycle. It is then parametrized for a benchmark terpolymer material. Model outputs are used to examine the system performance under each cycle as a function of temperature lift. The impact of electrical charge recovery efficiency on performance is then invesand to provide insight into system optimization requirements. Practical limitations of charge recovery circuits are discussed in the context of heat and work transfer in each cycle leg. Results indicate that electrical charge recovery efficiency greater than 95% is needed to achieve competitive system efficiency and that this is challenging with a Carnot cycle, despite its theoretical optimality. The Brayton and Otto cycles, in contrast, can achieve cooling efficiencies that approach the theoretical maximum.

This study investigates the correlation between the Edmonton Obesity Staging System (EOSS) and the occurrence of postoperative complications after medial thigh lift in formerly obese patients.A single-institution retrospective review of patients undergoing medial thigh lift between 2009 and 2019 after massive weight loss. Data on demography, comorbidities, surgery, and postoperative outcome were extracted from patients' charts. Patients were grouped into EOSS categories. Complications were classified into minor and major. Logistic regression analysis was performed to determine the association between risk factors and complications.One hundred and eight patients were included in the study. Complications occurred in 76 (70%) of the patients, most of which were minor (60/108, 56%). Complications increased with increasing EOSS stage, and all EOSS 3 patients had complications. Classification as EOSS 2 or 3 significantly associated with occurrence of postoperative complications (OR 99.3, p0.001) as well as minor and major complications individually (OR 3.1 and 6.5, p0.05). This effect was independent of body mass index (BMI), maximum BMI loss, type of weight loss, volume of liposuction, weight of resected tissue, and type of surgery.EOSS is a robust and independent predictor for postoperative complications in medial thigh lift surgery after massive weight loss.

THEPURPOSE.To consider the problems of controlling the energy efficiency of artificial oil lift. To conduct a comparative analysis of the approaches used to assess the level of energy efficiency and the possibility of energy saving. To submit to a modern possible energy efficiency control system. To identify an effective method for verifying energy efficiency indicators. To propose a concept of an automated control system for energy efficiency of artificial oil lift based on intelligent methods of data analysis.METHODS.Whensolvingtheproblem,themethodoffactoranalysisofspecificpowerconsumption,implementedina model, was used.RESULTS.Thearticledescribestherelevanceofthetopic,considersthefeaturesoftheuseofvariousindicatorsofenergyefficiency.A model of factors for specific power consumption has been developed. In this article, a concept of an automated energy efficiency control system based on intelligent methods has been proposed.CONCLUSION. Usingtheindicatorofspecificelectricityconsumptionforartificialoillift,asanindicatorofenergyefficiency,makesitpossibletoassessthecurrentlevelofenergyefficiencyandidentifythepotentialforfurtherenergysaving.To control the specific consumption of electricity at the mechanized stock of production wells, it is necessary to implement systemic energy metering, additional factor analysis of deviations from the planned values. Using of intelligent methods of data analysis selects the factors of deviation of the specific power consumption and ensures the reliability of energy efficiency control.

Response surface methodology was adopted to establish the mathematical model between the parameters (overlap ratio, Y-axis lift, and X-axis offset) and responses (non-fusion area, flatness ratio, and width of clad). The results indicated that the non-fusion area reduced at first and increased afterwards as overlap ratio decreased and Y-axis lift increased, while gradually reduced when overlap ratio increased and X-axis offset decreased. The flatness ratio gradually decreased by lowering the overlap ratio and raising the X-axis offset but gradually increased as Y-axis lift and X-axis offset lowered simultaneously. The clad width gradually reduced when overlap ratio or X-axis offset increased. A validation experiment was carried out with the target of minimizing the non-fusion area and maximizing the flatness ratio. The error rate for both responses was 7.7% and 3.6%, respectively. This article provides a theoretical basis for the forming control and prediction of double-layer and multi-track coatings by laser cladding.

The ability for ground vehicles to identify terrain types and characteristics can help provide more accurate localization and information-rich mapping solutions. Previous studies have shown the possibility of classifying terrain types based on proprioceptive sensors that monitor wheel-terrain interactions. However, most methods only work well when very strict motion restrictions are imposed including driving in a straight path with constant speed, making them difficult to be deployed on real-world field robotic missions. To lift this restriction, this letter proposes a fast, compact, and motion-robust, proprioception-based terrain classification method. This method uses common on-board UGV sensors and a 1D Convolutional Neural Network (CNN) model. The accuracy of this model was further improved by fusing it with a vision-based CNN that made classification based on the appearance of terrain. Experimental results indicated the final fusion models were highly robust with strong performance, with over 93% accuracy, under various lighting conditions and motion maneuvers.

A high precision and compact IOT based digital instrumentation setup to measure, display and record various tractor and implement system performance parameters was developed and installed on a 28.3 kW Tractor. The setup was capable of continuous monitoring and wirelessly transmitting tractor-implement performance parameters on a cloud platform such as engine speed, radiator fan speed, fuel consumption, draft, forward speed, lift arm angle, wheel slip, wheel slip, PTO speed, geo-location/position of the tractor, choking of seeds in the implement and vibrations experienced by the implement. For precision measurements, commercial transducers used in the system were calibrated and assessed under both static and dynamic conditions. The average calibration constant for fuel consumption, forward speed, lift arm angle and load cell were 0.00009804 L/pulse, 0.01610306 km/h/pulse, 0.056 mA/degree and 0.2575 mV/kN respectively. The system based on DataTaker DT 85 Data logger connected to a micro-computer through transducers capable of transferring data wirelessly was installed on John Deere 5038 tractor and was tested with a Spatially Modified No-Till Drill in agricultural field with varied implement depth.

We build a tractable SIR-macro-model with time-varying parameters and use it to explore various policy questions such as when to lift the state of emergency (SOE). An earlier departure from the SOE results in smaller output loss and more deaths in the short run. However, if the SOE is lifted too early, the number of new cases will surge and another SOE may need to be issued in the future, possibly resulting in both larger output loss and more deaths. That is, the tradeoff between output and infection that exists in the short run does not necessarily exist in the long run. Our model-based analysis—updated weekly since January 2021, frequently reported by media, and presented to policymakers on many occasions—has played a unique role in the policy response to the COVID-19 crisis in Japan.

In northern Canada, due to the harsh weather and high labor cost, contractors prefer to using modular construction approach to complete heavy industrial projects, where mobile crane are used for onsite module installations. In current practice, module lifts are often planned manually by rigging engineers. With a large number of heavy lifts to be analyzed per project, the planning process is tedious and error prone. This paper represents a data-driven crane management system with three features: (1) identification of design errors in lifting planning; (2) responses to design changes; and (3) dynamic 3D trajectory-based lifting visualization. It covers two types of crane operations: pick from a fixed location, and pick and walking operation. This developed system helps reduce lifting time and improves safety and quality, where various lifting scenarios need to be analyzed. The system has been implemented at a collaborator company for demonstration and validation.

We analyze the 25-year trajectory of Temporary Assistance for Needy Families (TANF), the nation’s cash safety net for families with children. Since its creation, TANF’s story has been one of greatl...

In many oil reservoirs worldwide, the downhole pressure does not have the ability to lift the produced fluids to the surface. In order to produce these fluids, pumps are used to artificially lift the fluids; this method is referred to as artificial lift. More than seventy percent of all currently producing oil wells are being produced by artificial lift methods. One of the most applied artificial lift methods is sucker rod pump. Sucker rod pumps are considered a well-established technology in the oil and gas industry and thus are easy to apply, very common worldwide, and low in capital and operational costs. Many advancements in technology have been applied to improve sucker rod pumps performance, applicability range, and diagnostics. With these advancements, it is important to be able to constantly provide an updated review and guide to the utilization of the sucker rod pumps. This research provides an updated comprehensive review of sucker rod pumps components, diagnostics methods, mathematical models, and common failures experienced in the field and how to prevent and mitigate these failures. Based on the review conducted, a new classification of all the methods that can fall under the sucker rod pump technology based on newly introduced sucker rod pump methods in the industry has been introduced. Several field cases studies from wells worldwide are also discussed in this research to highlight some of the main features of sucker rod pumps. Finally, the advantages and limitations of sucker rod pumps are mentioned based on the updated review. The findings of this study can help increase the understanding of the different sucker rod pumps and provide a holistic view of the beam rod pump and its properties and modeling.

When assisting a care receiver to transfer from one plane to another, a caregiver needs to hold up and move him/her. As a caregiver has to support the weight of one person, transfer assistance imposes a heavy physical burden on the caregiver. Particularly, in Japan, with an increasing elderly population and a decreasing young population, there are a few caregivers to assist numerous care receivers to transfer. In this scenario, it is an extremely vital issue to develop methods to reduce the burden of the caregivers when assisting care receivers to transfer. In this study, by focusing on the clothes that care receivers wear, we developed a transfer-assisting robot system by combining a dedicated posture-supporting wear and a mobile robot based on a lift mechanism.

In this study, we explore the changes in the earlobe segments following an extended superficial musculoaponeurotic system (SMAS) face-lift and neck lift. We proposed to delineate the effect of the cheek and neck skin tension vectors on the earlobe based on the amount of excised skin length. A retrospective study identified patients who underwent extended SMAS rhytidectomy performed by the senior author (A.M.) at the Cosmetic Plastic Surgery Institute (CPSI) from 2017 to 2020. A total of 34 North American Caucasians, who had preoperative and postoperative photographs available for comparison, were evaluated. Preoperative and postoperative cephalic (the distance from the intertragal notch to the otobasion inferius, abbreviated as I to O) and caudal earlobe segment (the distance from the otobasion inferius to the subaurale, abbreviated as O to S) heights were collected. The change from the postoperative to preoperative measurements was calculated. The effects of the degree of cheek skin (superior ear [SE]) and neck skin (mastoid peak [MP]) excision lengths were then determined by comparing the change in I to O and O to S. The postoperative attached cephalic segment (15.94 ± 1.02 mm) increased significantly compared with the preoperative attached cephalic segment (12.99 ± 1.03 mm). The postoperative free caudal segment (3.62 ± 0.81 mm) decreased significantly compared with the preoperative free caudal segment (5.44 ± 0.95 mm). The SE median was found to be 3.0 cm and the MP median was found to be 3.5 cm. I to O increased by 3.85 mm for SE ≤3.0 cm compared with only 1.57 mm for SE >3.0 cm. O to S decreased by 2.79 mm for SE ≤3.0 cm compared with only decrease of 0.14 mm for SE >3.0 cm. I to O increased by only 1.67 mm for MP < 3.5 cm. O to S decreased less dramatically by 0.55 mm for MP ≤3.5 cm compared with decrease of 2.39 mm for MP >3.5 cm. These data demonstrate that more aggressive SE >3.0 cm cheek excision lengths resulted in a protective effect on decreasing the free caudal segment of the earlobe. More aggressive excisions of the cheek demonstrate a protective effect on preserving the free earlobe caudal segment, whereas more aggressive neck skin excisions result in higher propensity for loss of the free earlobe caudal segment. In our study, we demonstrate findings observed with clinical observations that a face-lift and neck lift will result in increase in the attached cephalic earlobe segment height (I to O) and a decrease in caudal free earlobe segment height (O to S). These findings may assist plastic surgeons when trying to fine-tune the earlobe aesthetics during face-lift and neck lift. If the patient has a small free hanging earlobe, the more aggressive pull on the cheek flap will result in less reduction in the earlobe hang.

Given a solid 3D shape and a trajectory of it over time, we compute its swept volume - the union of all points contained within the shape at some moment in time. We consider the representation of the input and output as implicit functions, and lift the problem to 4D spacetime, where we show the problem gains a continuous structure which avoids expensive global searches. We exploit this structure via a continuation method which marches and reconstructs the zero level set of the swept volume, using the temporal dimension to avoid erroneous solutions. We show that, compared to other methods, our approach is not restricted to a limited class of shapes or trajectories, is extremely robust, and its asymptotic complexity is an order lower than standards used in the industry, enabling its use in applications such as modeling, constructive solid geometry, and path planning.

The user interfaces of control panels used for electronic automation have been limited to devices such as remote control, key pad and touch screen for a long time. These interfaces are not natural and nor flexible for users. Consumers are expecting natural efficient user interfaces. Recent improvements in sensor technology are now opening the path for developers to add gesture control to their products. This Project presents a switch control panel for Touch-free user interface using simple hand gestures technique to control operations of Elevator/Lift. This gesture-based switch control panel is not just limited to Elevator/Lift, but can also be implemented in other areas such as Vending machines, ATMs and many more with little changes in software & hardware if required. To use this interactive system based on hand gestures, one does not require any prerequisite knowledge as in the case of touch-screens, keyboard etc.

INTRODUCTION: A stula-in-ano, is a chronic abnormal communication, usually lined by granulation tissue, which runs outwards from the anorectal lumen. The standards of anal stula surgery are to obliterate the stula, prevent recurrence and maintain sphincter work. Ligation of Intersphincteric Fistula Tract (LIFT) is the most promising surgical technique based on secure closure of the internal opening and removal of the infected crypto glandular tissue through intersphincteric approach. AIMS: To compare the effectiveness of LIFT over SETON procedure based on Postoperative pain on day 1 and2, Short term recurrence, Healing, Procedural visits PATIENTS AND METHODS: A prospective, single centered, interventional study in 60 patients with stula-in-ano admitted to general surgical wards in Narayana Medical College and Hospital, Nellore. From November 2018 to November 2020. Patients were divided into two groups, group A including patients undergoing LIFT procedure and group B, including patients undergoing SETON placement of Fistula-in- ano. RESULTS: Maximum patients were in 41-60 years in the LIFT Group 18(60%), 51-60 years in the SETON group 12(40%). Maximum patients were male 21 in each group (70%), and female were 9 in each group (30%). In the present study, Visual Analog Scale (0,1,2,3) in LIFT group on POD 1, were 2, 20, 6, 2 and in SETON group on POD 1 were 0, 9, 16, 5 respectively. Similarly, visual analogue scale (0,1,2,3) in LIFT group on POD 2, were 19.8.3.0 and in SETON group on POD 2 were 5, 20, 5, 0respectively. Patients who underwent LIFT procedure had a satisfactory postoperative period and the wound healed in all the cases. CONCLUSION: we conclude that LIFT gives good outcomes in terms of Postoperative pain on day 1 and 2, wound healing rate, single time procedure and recurrence during our short follow-up period of 6 months.

This work is focused on understanding the impact of uncertainties on various input parameters on the lift production for a flapping-wing drone equipped with a vibratory-based actuation mechanism. Uncertainty and sensitivity analysis techniques are used to investigate output trends under various input distribution types and ranges to determine the critical parameters that should be considered during the design phase. Two cases are investigated in this work: The first considers a purely linear actuation mechanism, and the second includes a cubic nonlinear spring. Input parameters under consideration are prescribed with varying levels of uncertainties and distributions. Results show that as input uncertainty increases, the range of outputs quickly increases and that there is a high chance of optimal performance failure from the drone. In addition, it is shown that input forcing and excitation frequency are the most influential parameters when operating at resonance and that the excitation frequency alone is the dominant parameter in the off-resonance regime. Lastly, uncertainty in the nonlinear stiffness results in the possibility of the drone producing low lift. These results can be used by researchers and designers to properly design vibratory-based actuation mechanisms for flapping-wing drones by considering the more influential parameters and ensuring they are designed with optimal performance.

Consider the famous schoolboy’s dilemma: “Is the Lord omnipotent?” “Yes, omnipotent!” “Then can He create a stone that He cannot Himself lift?” (If God cannot create such a stone, then He is not om...

While it is well established that societal restrictions have been effective in reducing COVID-19 emergency demand, evidence also suggests an impact upon emergency demand not directly related to COVID-19 infection. Hospital planning may benefit from a greater understanding of this association and the ability to reliably forecast future levels of non-COVID-19 demand. Activity data for Accident and Emergency (A&E) attendances and emergency admissions were sourced for all hospitals within the Bristol, North Somerset and South Gloucestershire healthcare system. These were regressed upon publicly available mobility data obtained from Google's Community Mobility Reports for the local area. Seasonal trends were controlled for using time series decomposition. The models were used to predict non-COVID-19 emergency demand under the UK Government's plan to sequentially lift all restrictions by 21 June 2021, in addition to three alternative hypothetical relaxation strategies. Rates of public mobility within the local area were shown to account for 77% and 65% of the variance in non-COVID-19 related A&E attendances and emergency admissions respectively. Modelling supports an increase in emergency demand in line with the level and timing of societal restrictions, with significant increases to be expected upon the ending of all legal limits. This study finds that non-COVID-19 emergency demand associates with the level of societal restrictions, with rates of public mobility representing a key determinant. Through predictive modelling, healthcare systems can improve their demand forecasting in effectively managing hospital capacity.