Short-Term and Long-Term Outcomes among COVID-19 Survivors: A Multi-Center Prospective Observational Study

Background: Since the outbreak of the COVID-19 pandemic caused massive case fatalities across the world, people have been left with significant physical and mental disabilities, which has had an adverse impact on their quality of life. The objective of this study is to measure the short-term and long-term outcomes among COVID-19 survivors. Methods: This is a six-month-long multicentre prospective observational study, carried out in four specialized hospitals in the capital city Dhaka, where six hundred participants were enrolled by non-probability convenience sampling. Data were collected through three structured interviews, and follow-ups were done during discharge, at 1st month, and 6th month. An analytical study was done on demographic variables, socio-economic conditions, physical findings and outcomes. Data were analysed using Statistical Package for Social Sciences (SPSS). Results: A total of 600 participants were enrolled. The mean age was 49.83. Many participants belong to the age range of 31 to 40 years. More than two-thirds (72.7%) of participants were male, whereas 27.30% were female. Most patients admitted had mild and moderate COVID-19 symptoms (40% and 58%, respectively). Among short-term COVID complications, it was found that 43.3% of the participants complained of fatigue, 32.6% of depression, 24.7% of sleep disturbance, 19% of anxiety and, 5% memory loss. In long-term COVID complications the number reduced significantly: 5% of the participants complained of fatigue, 10% of depression, 2.7% of sleep disturbance, 7.3% of anxiety and, 2.7% memory loss. The severity of lung parenchymal disease also reduced in long term COVID symptoms. The study found a statistically significant relationship between age groups and CT severity index (χ2 = 9.458, p = 0.032). Most patients (29.2%) in the under-30 age group had a CT Severity Index score of 2 & 3 (29.2%). The important CT Severity Index scores for individuals aged 30 to 60 years were 3 and 4, accounting for 37.7% and 33.3%, respectively. In the over-60 age group, 40.8% of patients showed a CT Severity Index score of 4, showing a range of 51% - 75%. Conclusion: This study found that fatigue, depression, and sleep disturbances are prevalent among COVID-19 survivors;however, these symptoms generally reduce over time. Lung problems improved;however, some patients suffered from persistent effects. Older patients, especially those with pre-existing conditions, suffer from more severe outcomes. These findings underscore the need for ongoing care for COVID-19 survivors.

一种基于long short-term memory的唇语识别方法

唇动视觉信息是说话内容的重要载体。受嘴唇外观、背景信息和说话习惯等影响,即使说话者说相同的内容,唇动视觉信息也会相差很大。为解决唇语视觉信息多样性的问题,提出一种基于long short-term memory(LSTM)的新的唇语识别方法。以往大多数的方法从嘴唇外表信息入手。本方法用嘴唇关键点坐标描述嘴唇形变信息作为唇语视频的特征,它具有类内一致性和类间区分性的特点。然后利用LSTM对特征进行时序编码,它能学习具有区分性和泛化性的空间-时序特征。在公开的唇语数据集GRID、MIRACL-VC和Oulu VS上对本方法做了针对分割的单词或短语的说话者独立的唇语识别评估。在GRID和MIRACL-VC上,本方法的准确率比传统方法至少高30%;在Oulu VS上,本方法的准确率接近于最优结果。以上实验结果表明,本文提出的基于LSTM的唇语识别方法有效地解决了唇语视觉信息多样性的问题。

Long-term effects of early antibiotic intervention on blood parameters,apparent nutrient digestibility, and fecal microbial fermentation profile in pigs with different dietary protein levels

Backgroud： This study aimed to determine the effects of early antibiotic intervention（EAI） on subsequent blood parameters, apparent nutrient digestibility, and fecal fermentation profile in pigs with different dietary crude protein（CP） levels. Eighteen litters of piglets（total 212） were randomly allocated to 2 groups and were fed a creep feed diet with or without in-feed antibiotics（olaquindox, oxytetracycline calcium and kitasamycin） from postnatal d 7 to d 42. On d 42, the piglets within the control or antibiotic group were mixed, respectively, and then further randomly assigned to a normal-（20%, 18%, and 14% CP from d 42 to d 77, d 77 to d 120, and d 120 to d 185,respectively） or a low-CP diet（16%, 14%, and 10% CP from d 42 to d 77, d 77 to d 120, and d 120 to d 185,respectively）, generating 4 groups. On d 77（short-term） and d 185（long-term）, serum and fecal samples were obtained for blood parameters, microbial composition and microbial metabolism analysis.Results： EAI increased（P 〈 0.05） albumin and glucose concentrations in low-CP diet on d 77, and increased（P 〈 0.05） urea concentration in normal-CP diet. On d 185, EAI increased（P 〈 0.05） globulin concentration in normal-CP diets, but decreased glucose concentration. For nutrient digestibility, EAI increased（P 〈 0.05）digestibility of CP on d 77. For fecal microbiota, the EAI as well as low-CP diet decreased（P 〈 0.05） E. coli count on d 77. For fecal metabolites, on d 77, EAI decreased（P 〈 0.05） total amines concentration but increased skatole concentration in low-CP diet. On d 185, the EAI increased（P 〈 0.05） putrescine and total amines concentrations in low-CP diets but reduced（P 〈 0.05） in the normal-CP diets. The low-CP diet decreased the concentrations of these compounds.Conclusions： Collectively, these results indicate that EAI has short-term effects on the blood parameters and fecal microbial fermentation profile. The effects of EAI varied between CP levels, which was characterized by the significant alteration of glucose and putrescine concentration.

Tool Health Condition Recognition Method for High Speed Milling of Titanium Alloy Based on Principal Component Analysis (PCA) and Long Short Term Memory (LSTM)

The healthy condition of the milling tool has a very high impact on the machining quality of the titanium components.Therefore,it is important to recognize the healthy condition of the tool and replace the damaged cutter at the right time.In order to recognize the health condition of the milling cutter,a method based on the long short term memory(LSTM)was proposed to recognize tool health state in this paper.The various signals collected in the tool wear experiments were analyzed by time-domain statistics,and then the extracted data were generated by principal component analysis(PCA)method.The preprocessed data extracted by PCA is transmitted to the LSTM model for recognition.Compared with back propagation neural network(BPNN)and support vector machine(SVM),the proposed method can effectively utilize the time-domain regulation in the data to achieve higher recognition speed and accuracy.

Conditional Random Field Tracking Model Based on a Visual Long Short Term Memory Network

In dense pedestrian tracking,frequent object occlusions and close distances between objects cause difficulty when accurately estimating object trajectories.In this study,a conditional random field tracking model is established by using a visual long short term memory network in the three-dimensional(3D)space and the motion estimations jointly performed on object trajectory segments.Object visual field information is added to the long short term memory network to improve the accuracy of the motion related object pair selection and motion estimation.To address the uncertainty of the length and interval of trajectory segments,a multimode long short term memory network is proposed for the object motion estimation.The tracking performance is evaluated using the PETS2009 dataset.The experimental results show that the proposed method achieves better performance than the tracking methods based on the independent motion estimation.

Long Short-Term Memory Recurrent Neural Network-Based Acoustic Model Using Connectionist Temporal Classification on a Large-Scale Training Corpus

A Long Short-Term Memory(LSTM) Recurrent Neural Network(RNN) has driven tremendous improvements on an acoustic model based on Gaussian Mixture Model(GMM). However, these models based on a hybrid method require a forced aligned Hidden Markov Model(HMM) state sequence obtained from the GMM-based acoustic model. Therefore, it requires a long computation time for training both the GMM-based acoustic model and a deep learning-based acoustic model. In order to solve this problem, an acoustic model using CTC algorithm is proposed. CTC algorithm does not require the GMM-based acoustic model because it does not use the forced aligned HMM state sequence. However, previous works on a LSTM RNN-based acoustic model using CTC used a small-scale training corpus. In this paper, the LSTM RNN-based acoustic model using CTC is trained on a large-scale training corpus and its performance is evaluated. The implemented acoustic model has a performance of 6.18% and 15.01% in terms of Word Error Rate(WER) for clean speech and noisy speech, respectively. This is similar to a performance of the acoustic model based on the hybrid method.

Short-and long-term behaviors of drifts in the Callovo-Oxfordian claystone at the Meuse/Haute-Marne Underground Research Laboratory

Since 2000, the French National Radioactive Waste Management Agency （ANDRA） has been constructing an Underground Research Laboratory （URL） at Bure （east of the Paris Basin） to perform experiments in order to obtain in situ data necessary to demonstrate the feasibility of geological repository in the Callovo- Oxfordian claystone. An important experimental program is planned to characterize the response of the rock to different drift construction methods, Before 2008, at the main level of the laboratory, most of the drifts were excavated using pneumatic hammer and supported with rock bolts, sliding steel arches and fiber shotcrete. Other techniques, such as road header techniques, stiff and flexible supports, have also been used to characterize their impacts. The drift network is developed following the in situ major stresses. The parallel drifts are separated enough so as they can be considered independently when their hydromechanical （HM） behaviors are compared. Mine-by experiments have been performed to measure the HM response of the rock and the mechanical loading applied to the support system due to the digging and after excavation. Drifts exhibit extensional （mode I） and shear fractures （modes II and III） induced by excavation works. The extent of the induced fracture networks depends on the drift orientation versus the in situ stress field. This paper describes the drift convergence and deformation in the surrounding rock walls as function of time and the impact of different support methods on the rock mass behavior. An observation based method is finally applied to distinguish the instantaneous and time-dependent parts of the rock mass deformation around the drifts.

LONG-TERM EFFECT OF HOMOHARRINGTONINE ON CHRONIC GRANULOCYTIC LEUKEMIA

Objective: To observe the long-term effect of homoharringtonine (HHT) on chronic granulocytic leukemia (CGL) and its pharmacological mechanism. Methods: 76 patients with newly diagnosed early chronic phase CGL received treatment of merely 1.5 mg/m2 daily HHT for induction remission and long-term maintenance treatment. The apoptosis rate of bone marrow CD34+ cells induced by HHT was assayed with flow cytometer. Results: 86.8% patients achieved CHR, 13.2% patients PHR and 31.8% patients got cytogenetic response in HHT treatment group, which was longer than 31 (8-54) months in hydroxyurea (HU) group (P<0.05). The effect of apoptosis induction HHT was stronger on CGL-CP patients bone marrow CD34+ cells than on normal person bone marrow CD34+ cells. Conclusion: HHT is a very effective drug for remission induction and long-term maintenance treatment in early chronic phase CGL patients.

The Impact of Meteorological Factors on the Short-term Cumulative Effect of Air Particulate in Tianjin

In order to reveal the rapid increase mechanism of particulate concentration in short time,a notion of short-term cumulative effect of air particulate is defined as the significant increase of pollutant concentration in a short time under the condition of breeze,stable weather and constant emission caused by human being's activities. Subsequently,an index of short-term cumulative effect is established with air diffusive equation,and then the macro-scale meteorological situation and micro-scale factors of forming the short-term cumulative effect are discussed with the observation data. The macro-scale meteorological variables contain upper-level weather situations and surface weather situations. The micro-scale factors mainly include the boundary-layer height and boundary-layer stability. The analyses show that boundary-layer factors and weather variables have a significant influence on the short-term cumulative effect. The notion of short-term cumulative effect will play an important role in interpreting the severe pollution weather.

NUMERICAL STUDY OF SHORT TERM EFFECT OF SST ANOMALIES

Using a 5-layer P- o mixed coordinates primitive equations model, a process of heavy rain is simulated that occurred over the middle-and lower-reaches of the Changjiang River on July 1- 2, 1991 and numerical experiments are done of the effects of sea surface temperature (SST) anomalies over different waters on the precipitation. The result has shown that the appearance of SST anomaly is followed in a short term (2 or 3 days) by. A change in the pattern of circulation as well as in precipitation to some extent.

Short-Term Relay Quality Prediction Algorithm Based on Long and Short-Term Memory

The fraction defective of semi-finished products is predicted to optimize the process of relay production lines, by which production quality and productivity are increased, and the costs are decreased. The process parameters of relay production lines are studied based on the long-and-short-term memory network. Then, the Keras deep learning framework is utilized to build up a short-term relay quality prediction algorithm for the semi-finished product. A simulation model is used to study prediction algorithm. The simulation results show that the average prediction absolute error of the fraction is less than 5%. This work displays great application potential in the relay production lines.

Predicting and Curing Depression Using Long Short Term Memory and Global Vector

In today’s world, there are many people suffering from mentalhealth problems such as depression and anxiety. If these conditions are notidentified and treated early, they can get worse quickly and have far-reachingnegative effects. Unfortunately, many people suffering from these conditions,especially depression and hypertension, are unaware of their existence until theconditions become chronic. Thus, this paper proposes a novel approach usingBi-directional Long Short-Term Memory (Bi-LSTM) algorithm and GlobalVector (GloVe) algorithm for the prediction and treatment of these conditions.Smartwatches and fitness bands can be equipped with these algorithms whichcan share data with a variety of IoT devices and smart systems to betterunderstand and analyze the user’s condition. We compared the accuracy andloss of the training dataset and the validation dataset of the two modelsnamely, Bi-LSTM without a global vector layer and with a global vector layer.It was observed that the model of Bi-LSTM without a global vector layer hadan accuracy of 83%,while Bi-LSTMwith a global vector layer had an accuracyof 86% with a precision of 86.4%, and an F1 score of 0.861. In addition toproviding basic therapies for the treatment of identified cases, our model alsohelps prevent the deterioration of associated conditions, making our methoda real-world solution.

Long Term Application of a Vehicle-Based Health Monitoring System to Short and Medium Span Bridges and Damage Detection Sensitivity

Largest portion of the bridge stock in almost any country and bridge owning organisation consists on ordinary bridges that has short or medium spans and are now deteriorating due to aging, etc. Therefore, it is becoming an important social concern to develop and put to practical use simple and efficient health monitoring systems for existing short and medium span (10 - 30 m) bridges. In this paper, one practical solution to the problem for condition assessment of short and medium span bridges was discussed. A vehicle-based measurement with a public bus as part of a public transit system (called “Bus monitoring system”) has been developed to be capable of detecting damage that may affect the structural safety of a bridge from long term vibration measurement data collected while the vehicle (bus) crossed the target bridges. This paper systematically describes how the system has been developed. The bus monitoring system aims to detect the transition from the damage acceleration period, in which the structural safety of an aged bridge declines sharply, to the deterioration period by continually monitoring the bridge of interest. To evaluate the practicality of the newly developed bus monitoring system, it has been field-tested over a period of about four years by using an in-service fixed-route bus operating on a bus route in the city of Ube, Yamaguchi Prefecture, Japan. The verification results thus obtained are also described in this paper. This study also evaluates the sensitivity of “characteristic deflection”, which is a bridge (health) condition indicator used by the bus monitoring system, in damage detection. Sensitivity of “characteristic deflection” is verified by introducing artificial damage into a bridge that has ended its service life and is awaiting removal. As the results, it will be able to make a rational long-term health monitoring system for existing short and mediumspan bridges, and then the system helps bridge administrators to establish the rational maintenance strategies.

Statistical Transformation Indicators of Short-Term to Long-Term Using Flood Regional Coefficients (Case Study: East Azarbaijan Province, Iran)

Changing contexts in a long-term and short-term perspective should be managed within an integrated risk management framework that accounts for both temporary management strategies and permanent preventive measures to reduce the impact of natural hazard processes. In this study, statistical transformation indicators of short-term (20 year) to long-term (30 year) used flood regional coefficients. After the tests of data validation and the reconstruction of missing and outlier data, the data of 18 hydrometric stations were completed for 30 years (1985 to 2014). In the next phase, the return period values were prepared for 20-year and 30-year statistical periods (1985 to 2004 and 1985 to 2014) using the HYFA software. Thus the 20-year to 30-year ratio for various return period discharges obtained and these dimensionless values were plotted for the return periods of 2, 5, 10, 20, 50 and 100 years, also fitted the logarithmic trend line and the values of coefficients of the relationship were obtained. The statistics including average, standard deviation, coefficient of variation (CV), skewness coefficient (CS) and Kurtosis coefficient (CK) were calculated for 20-year data period for each station and we identified the statistics as independent parameters and the coefficients of A and B as dependent parameter, thus analyzed using linear multivariate regression, and regional factors were obtained. In the hydrometric station with 17-027 code, the discharge using the regional factors was calculated and compared with the discharge values of 30 years data. The results showed that there is little difference between the observed and estimated values from regional factors thus this method can be used in projects that require at least 30 years of data.

Study on the operation effect of long term care insurance system in Qingdao

Population aging has become a global social problem, the problem in our country has become the core of the aging problem. With the gradual aging of the elderly, loss of energy, loss of energy has become the norm for the elderly or sick elderly. According to the Ministry of Civil Affairs statistics, as of the end of 2014, the number of disabled elderly in China reached 35 million, about 90% of the disabled elderly need professional care services and professional treatment to ease the pain. In order to deal with the social problems brought about by the aging of the population, in July 1, 2012, Qingdao City, the first in the country to establish a long-term health care insurance system, has taken a key step to crack the problem of aging. In this paper, the situation of Qingdao long term care insurance system as the research object, taking Qingdao city as study sites, according to statistical data analysis of the implementation effect of long-term local health care policy, and through questionnaires and interviews in the form of local residents to participate in the investigation of awareness, and perception. At the same time, the results of the survey on long-term health care insurance system in Qingdao, the operation effect of the overall analysis.

Clinical Observation on the Improved Short-Term Effects of Anti-Tumor Purified Chinese Medicine Injection Ai-Jing for 138 Cases with Malignant Tumors

The subjects of this study were to observe the improved short-term effects of anti-tumor purified Chinese medicine injection Ai-Jing for 138 cases with malignant tumors. This was a multi-center clinical study, and a total of 138 patients included 96 males and 42 females, with the age from 60 to 76 years. Ai-Jing has obtained the Chinese invention patent since 2008 (ZL991-03528.3). A novel technique acupoint injection method was adopted. Except for lung cancer, patients with other malignant tumors were injected once every other day, 2 ml each time. A course of treatment needs 6 Ai-Jing injections, lung cancer patients need 10 - 20 Ai-Jing injections. At the same time, patients were treated with traditional medicine decoction. Due to the limited number of cases, cure rate, recovery rate and remission rate were calculated as a whole, respectively 18.12%, 44.20% and 32.15%. All the invalid patients were lung cancer, accounting for 16.67% of the patients treated with lung cancer, and the total treatment inefficiency was 6.52%. Conclusion: Chinese Medicine Injection Ai-Jing extracts the effective components of anti-cancer and tumorigenesis, and has the effects of anti-cancer and tumorigenesis, anti-inflam-matory and analgesic, and repairing body damage, with small toxic and side effects and low cost.

Analyses of fear memory in Arc/Arg3.1-deficient mice: intact short-term memory and impaired long-term and remote memory

Activity-regulated cytoskeleton-associated protein (Arc/Arg3.1) was originally identified in patients with seizures. It is densely distributed in the hip-pocampus and amygdala in particular. Because the expression of Arc/Arg3.1 is regulated by nerve in-puts, it is thought to be an immediate early gene. As shown both in vitro and in vivo, Arc/Arg3.1 is in-volved in synaptic consolidation and regulates some forms of learning and memory in rats and mice [1,2]. Furthermore, a recent study suggests that Arc/Arg3.1 may play a significant role in signal transmission via AMPA-type glutamate receptors [3-5]. Therefore, we conducted a detailed analysis of fear memory in Arc/Arg3.1-deficient mice. As previously reported, the knockout animals exhib-ited impaired fear memory in both contextual and cued test situations. Although Arc/Arg3.1-deficient mice showed almost the same performance as wild-type littermates 4 hr after a conditioning trial, their performance was impaired in the retention test after 24 hr or longer, either with or without reconsolidation. Immunohistochemical analyses showed an abnormal density of GluR1 in the hip-pocampus of Arc/Arg3.1-deficient mice;however, an application of AMPA potentiator did not improve memory performance in the mutant mice. Memory impairment in Arc/Arg3.1-deficient mice is so ro-bust that the mice provide a useful tool for devel-oping treatments for memory impairment.

Short-Term and Long-Term Price Forecasting Models for the Future Exchange of Mongolian Natural Sea Buckthorn Market

Sea buckthorn market floated uncertainly within a narrow range. The market situation provided upward pressure on prices, and producer and consumer interest were poor, coupled with weak prices in the regional markets. The objectives of the study are: 1) to estimate the relationship between wild Sea buckthorn (SB) price and Supply, Demand, while some other factors of crude oil price and exchange rate by using simultaneous Supply-Demand and Price system equation and Vector Error Correction Method (VECM);2) to forecast the short-term and long-term SB price;3) to compare and evaluate the price forecasting models. Firstly, the data was analyzed by Ferris and Engle-Granger’s procedure;secondly, both price forecasting methodologies were tested by Pindyck-Rubinfeld and Makridakis’s procedure. The result shows that the VECM model is more efficient using yearly data;a short-term price forecast decreases, and a long-term price forecast is predicted to increase the Mongolian Sea buckthorn market.

Comparison of short- with long-term regeneration results after digital nerve reconstruction with musclein-vein conduits

Muscle-in-vein conduits are used alternatively to nerve grafts for bridging nerve defects. The purpose of this study was to examine short- and long-term regeneration results after digital nerve reconstruction with muscle-in-vein conduits. Static and moving two-point discriminations and Semmes-Weinstein Monofilaments were used to evaluate sensory recovery 6–12 months and 14–35 months after repair of digital nerves with muscle-in-vein in 7 cases. Both follow-ups were performed after clinical signs of progressing regeneration disappeared. In 4 of 7 cases, a further recovery of both two-point discriminations and in another case of only the static two-point discrimination of 1–3 mm could be found between the short-term and long-term follow-up examination. Moreover, a late recovery of both two-point discriminations was demonstrated in another case. Four of 7 cases showed a sensory improvement by one Semmes-Weinstein Monofilaments. This pilot study suggests that sensory recovery still takes place even when clinical signs of progressing regeneration disappear.

A LONG TERM EFFECT EVALUATION OF TOTAL HIP PROSTHETIC REPLACEMENT

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