Frequently cutting restriction enzymes: Clearing the fog to see the ends

Telomeres, which are found at the ends of eukaryotic chromosomes, are composed of tandem arrays of repetitive sequences and safeguard genomic stability. Previous studies have revealed that telomeric repeats are also present at internal chromosomal loci in many eukaryotes. However, the biological role of these interstitial telomeric sequences (ITSs) remains unknown. The integrity of telomeric length and chromatin structure is required for telomere stability. However, the study of these telomeric features can be impeded by the presence of ITSs. Frequently cutting restriction enzymes have been revealed to be very useful tools for the study of the length and chromatin structure of telomeres independent of the presence of ITSs.

Frequently Asked Questions About Ancient Olympics

1.Where did the Olympic gamescome from?There are many different stories about the be-ginning of the Olympics.One myth says that the guardians of the infantgod Zeus held the first footrace,or that Zeus himselfstarted the Games to celebrate his victory over his fa-ther Cronus for control of the world.Another tradi-tion states that after the Greek hero Pelops won achariot race against King Oenomaus to marry Oeno-

Oral mucositis induced by risperidone:rare side effect of a frequently prescribed medication

Risperidone is a safe second-generation antipsychotic which is rarely associated with the emergence of a few adverse effects,such as oral lesions and stomatitis.We report the case of a 77-year-old woman affected by a neurocognitive disorder with psychotic features and treated with risperidone 2 mg/day.After 1 week,she showed a burning mouth syndrome with oral lesions and risperidone was discontinued.Antipsychotic-induced oral ulcerations may be caused by the reduction of saliva protection with minor adverse effects related to oral movement disorders or impairment of the bacterial flora of saliva.

Usefulness of mizoribine administration in children with frequently relapsing nephrotic syndrome, and the relationship between pharmacokinetic parameters and efficacy: a multicenter prospective cohort study in China

Background Mizoribine (MZR) is an immunosuppressant used to treat adult nephropathy.There is little experience with the drug in treating Chinese children with frequently relapsing nephrotic syndrome (FRNS).We investigated the efficacy and safety for treating MZR with FRNS.Furthermore,the relationship between efficacy and serum concentration was investigated.Methods A prospective multicenter observational 12-month study was performed for evaluating the usefulness of MZR with FRNS.Serum MZR concentration was measured,and the relationships between pharmacokinetic parameters (Cmax,AUC),number of relapses,and urinary protein were evaluated.Results Eighty-two pediatric patients from four hospitals were treated with MZR and prednisone.MZR treatment significantly reduced the number of relapses and steroid doses.A correlation between pharmacokinetic parameters and relapses was observed,which fits well with the sigmoidal Emax model.Even in the relationship between pharmacokinetic parameters and urinary proteins,it was recognized that there was a threshold in the pharmacokinetic parameters for the therapeutic effect similar to the results obtained with the sigmoidal Emax model.Eleven patients (13.4%) experienced mild adverse events.Conclusions MZR therapy was effective in reducing the number of relapses and steroid doses.No severe adverse reactions were observed.Therapeutically effective serum concentrations were estimated to be Cmax > about 2 μg/mL or AUC > about 10 lag h/mL.MZR and steroid treatment were effective and safe for pediatric FRNS.

Thoracoscopic resection of giant left atrial appendage aneurysm: A case report

Left atrial appendage aneurysm(LAAA)was first reported in the 1960s.1 LAAA is a rare condition,with just over 100 congenital or acquired cases reported to date.2 LAAA is frequently diagnosed incidentally during echocardiography or computed tomography(CT)scans.Most patients with LAAA are asymptomatic,while a few exhibit nonspecific symptoms,such as dyspnea,palpitation,and chest tightness.Patients with LAAA frequently present with atrial arrhythmias and systemic thromboembolism,such as stroke or multiorgan infarctions,due to the formation of a left atrial appendage thrombus.3 The lesion may be cured using aneurysm resection.Considering it as the potential cause of atrial arrhythmias and thromboembolism,the lesion must be identified on time and cured using a suitable treatment approach.

A related degree-based frequent pattern mining algorithm for railway fault data

It is of great significance to improve the efficiency of railway production and operation by realizing the fault knowledge association through the efficient data mining algorithm.However,high utility quantitative frequent pattern mining algorithms in the field of data mining still suffer from the problems of low time-memory performance and are not easy to scale up.In the context of such needs,we propose a related degree-based frequent pattern mining algorithm,named Related High Utility Quantitative Item set Mining(RHUQI-Miner),to enable the effective mining of railway fault data.The algorithm constructs the item-related degree structure of fault data and gives a pruning optimization strategy to find frequent patterns with higher related degrees,reducing redundancy and invalid frequent patterns.Subsequently,it uses the fixed pattern length strategy to modify the utility information of the item in the mining process so that the algorithm can control the length of the output frequent pattern according to the actual data situation and further improve the performance and practicability of the algorithm.The experimental results on the real fault dataset show that RHUQI-Miner can effectively reduce the time and memory consumption in the mining process,thus providing data support for differentiated and precise maintenance strategies.

Exploring the Spectacular Scenery of MAGQU ALONG NATIONAL HIGHWAY 317

May marks the beginning of the annual harvest of caterpillar fungus in Bachen County of Nagqu City,Xizang Autonomous Region.As the rainy season sets in,the vast grasslands receive frequent downpours.Regardless of whether you are in the downtown area or out on the grasslands,you can frequently witness stunning rainbows.

Favorable Policies For Titanium Tube Industry Are Unveiled Frequently in 2016

For the titanium tube industry in 2016,the widespread loss in the industry in 2015 will quicken the adjustment pace of product structure in the tube market,and create new industrial situation;furthermore,the'One Belt,One Road'plan in the'Thirteenth Five Year'Plan will also boost demand in the tube market.Meanwhile,due to the tremendous base in capacity and output,and excessively long absorption time;coupled with heavy

Impact of sarcopenia on the progression of nonalcoholic fatty liver disease: a frequently forgotten association

The development of sarcopenia in patients with chronic liver disease has been recognized as a predictor of poor outcome.Sarcopenia,or the progressive loss of skeletal muscle mass begins to manifest in the early stages of chronic liver disease and worsens with progression to advanced liver disease with a prevalence approaching 60%in patients with end-stage liver disease(1).

High Utility Periodic Frequent Pattern Mining in Multiple Sequences

Periodic patternmining has become a popular research subject in recent years;this approach involves the discoveryof frequently recurring patterns in a transaction sequence. However, previous algorithms for periodic patternmining have ignored the utility (profit, value) of patterns. Additionally, these algorithms only identify periodicpatterns in a single sequence. However, identifying patterns of high utility that are common to a set of sequencesis more valuable. In several fields, identifying high-utility periodic frequent patterns in multiple sequences isimportant. In this study, an efficient algorithm called MHUPFPS was proposed to identify such patterns. To addressexisting problems, three new measures are defined: the utility, high support, and high-utility period sequenceratios. Further, a new upper bound, upSeqRa, and two new pruning properties were proposed. MHUPFPS usesa newly defined HUPFPS-list structure to significantly accelerate the reduction of the search space and improvethe overall performance of the algorithm. Furthermore, the proposed algorithmis evaluated using several datasets.The experimental results indicate that the algorithm is accurate and effective in filtering several non-high-utilityperiodic frequent patterns.

Association RuleMining Frequent-Pattern-Based Intrusion Detection in Network

In the network security system,intrusion detection plays a significant role.The network security system detects the malicious actions in the network and also conforms the availability,integrity and confidentiality of data informa-tion resources.Intrusion identification system can easily detect the false positive alerts.If large number of false positive alerts are created then it makes intrusion detection system as difficult to differentiate the false positive alerts from genuine attacks.Many research works have been done.The issues in the existing algo-rithms are more memory space and need more time to execute the transactions of records.This paper proposes a novel framework of network security Intrusion Detection System(IDS)using Modified Frequent Pattern(MFP-Tree)via K-means algorithm.The accuracy rate of Modified Frequent Pattern Tree(MFPT)-K means method infinding the various attacks are Normal 94.89%,for DoS based attack 98.34%,for User to Root(U2R)attacks got 96.73%,Remote to Local(R2L)got 95.89%and Probe attack got 92.67%and is optimal when it is compared with other existing algorithms of K-Means and APRIORI.

Hybrid Recommender System Using Systolic Tree for Pattern Mining

A recommender system is an approach performed by e-commerce for increasing smooth users’experience.Sequential pattern mining is a technique of data mining used to identify the co-occurrence relationships by taking into account the order of transactions.This work will present the implementation of sequence pattern mining for recommender systems within the domain of e-com-merce.This work will execute the Systolic tree algorithm for mining the frequent patterns to yield feasible rules for the recommender system.The feature selec-tion's objective is to pick a feature subset having the least feature similarity as well as highest relevancy with the target class.This will mitigate the feature vector's dimensionality by eliminating redundant,irrelevant,or noisy data.This work pre-sents a new hybrid recommender system based on optimized feature selection and systolic tree.The features were extracted using Term Frequency-Inverse Docu-ment Frequency(TF-IDF),feature selection with the utilization of River Forma-tion Dynamics(RFD),and the Particle Swarm Optimization(PSO)algorithm.The systolic tree is used for pattern mining,and based on this,the recommendations are given.The proposed methods were evaluated using the MovieLens dataset,and the experimental outcomes confirmed the efficiency of the techniques.It was observed that the RFD feature selection with systolic tree frequent pattern mining with collaborativefiltering,the precision of 0.89 was achieved.

基于HowNet语义相似度的FAQ研究

FAQ是网站提供在线帮助的主要手段。利用检索机制根据用户提出的问题建立一个候选问句集,利用知网研究了用户问句和候选问句之间的相似度,从中找出最相似的问句,并将相应答案返回给用户。实验表明,该方法提高了问句匹配的准确率。

Backward Support Computation Method for Positive and Negative Frequent Itemset Mining

Association rules mining is a major data mining field that leads to discovery of associations and correlations among items in today’s big data environment. The conventional association rule mining focuses mainly on positive itemsets generated from frequently occurring itemsets (PFIS). However, there has been a significant study focused on infrequent itemsets with utilization of negative association rules to mine interesting frequent itemsets (NFIS) from transactions. In this work, we propose an efficient backward calculating negative frequent itemset algorithm namely EBC-NFIS for computing backward supports that can extract both positive and negative frequent itemsets synchronously from dataset. EBC-NFIS algorithm is based on popular e-NFIS algorithm that computes supports of negative itemsets from the supports of positive itemsets. The proposed algorithm makes use of previously computed supports from memory to minimize the computation time. In addition, association rules, i.e. positive and negative association rules (PNARs) are generated from discovered frequent itemsets using EBC-NFIS algorithm. The efficiency of the proposed algorithm is verified by several experiments and comparing results with e-NFIS algorithm. The experimental results confirm that the proposed algorithm successfully discovers NFIS and PNARs and runs significantly faster than conventional e-NFIS algorithm.

Uncharted Territory: Frequent Relapsing, Steroid Sensitive Secondary Minimal Change Nephrotic Syndrome Cause by Solid Tumor of the Gastro-Esophageal Junction —(Case Presentation and Review of the Literature)

We reported a biopsy proved case of minimal change nephrotic syndrome in a 72-year-old patient. The minimal change nephrotic syndrome has been steroid sensitive, but the patient had 7 relapses over a span of 5 years. Each time the dose of steroid is tapered, a relapse of the nephrotic syndrome occurred. Eventually, the patient was complaining of dysphagia and difficulty swallowing. Hospital work-up with barium swallow, endoscopy, and CT of the chest, abdomen and pelvis, revealed a focal stenotic lesion with mild to moderate esophageal dysmotility 7/15/2022. A diagnosis of an ulcerating lesion with biopsy confirmed a neuro-endocrine carcinoma of the gastro-esophageal junction was entertained. The CT of the chest/abdomen/pelvis, 7/19/2022, has shown, an esophageal mass of 5.1 × 5.6 × 7 cm of the gastro-esophageal junction with ulceration. No evidence of spread beyond the esophagus and stomach. The histology revealed a poorly differentiated neuroendocrine tumor of the gastro-esophageal junction. The patient underwent several rounds of chemotherapy, radiation, and surgery culminating in tumor control. His nephrotic syndrome was resolved after the tumor has been controlled by surgery and chemotherapy.

Quantum Algorithm for Mining Frequent Patterns for Association Rule Mining

Maximum frequent pattern generation from a large database of transactions and items for association rule mining is an important research topic in data mining. Association rule mining aims to discover interesting correlations, frequent patterns, associations, or causal structures between items hidden in a large database. By exploiting quantum computing, we propose an efficient quantum search algorithm design to discover the maximum frequent patterns. We modified Grover’s search algorithm so that a subspace of arbitrary symmetric states is used instead of the whole search space. We presented a novel quantum oracle design that employs a quantum counter to count the maximum frequent items and a quantum comparator to check with a minimum support threshold. The proposed derived algorithm increases the rate of the correct solutions since the search is only in a subspace. Furthermore, our algorithm significantly scales and optimizes the required number of qubits in design, which directly reflected positively on the performance. Our proposed design can accommodate more transactions and items and still have a good performance with a small number of qubits.

LFU算法的ASIC实现

为ASIC实现内存管理中页面替换的LFU算法,基于TSMC公司0.18μm的单元库,用标准逻辑单元库实现LFU算法.通过研究一组数中的最小值检出和最小值地址检出的逻辑规律,简化逻辑,减小了电路规模.通过控制关键路径的级数,达到了减少延迟,提高运行速度的目的.给出了版图和静态时序分析结果.

Fast FP-Growth for association rule mining

In this paper, we propose an efficient algorithm, called FFP-Growth (shortfor fast FP-Growth) , to mine frequent itemsets. Similar to FP-Growth, FFP-Growth searches theFP-tree in the bottom-up order, but need not construct conditional pattern bases and sub-FP-trees,thus, saving a substantial amount of time and space, and the FP-tree created by it is much smallerthan that created by TD-FP-Growth, hence improving efficiency. At the same time, FFP-Growth can beeasily extended for reducing the search space as TD-FP-Growth (M) and TD-FP-Growth (C). Experimentalresults show that the algorithm of this paper is effective and efficient.

A patient presenting painful chest wall swelling: Tietze syndrome

Dear editor,Patients frequently visit the emergency room with acute chest pain.While some potentially life-threatening disorders may cause the pain,in approximately 80%of cases,the chest pain source is benign,and musculoskeletal chest pain accounts for nearly 20%– 50%of those cases.^[1–6]Thus,pain caused by benign and pathological conditions of the chest wall encountered in the emergency department is sometimes incorrectly attributed to angina pectoris or pleuritic and other serious cardiopulmonary diseases.

Condition Identification Based on Vibration Measurements for Free Spanning Submarine Pipelines

Free spanning pipelines are suspended between two points on an uneven seaffoor. The variations of structural conditions, such as the changes in soil property, flow velocity, axial force and span length etc., directly affect working performance of the whole submarine pipeline system. But until now few researches have focused on condition identification for free span （CIFS）. A method to identify the operational conditions of free spanning submarine pipelines based on vibration measurements is proposed in this paper. Firstly, the ill-posedness of CIFS is analyzed in detail. Secondly, the framework for CIFS based on the nonlinear kernel discriminant analysis （KDA） is established. Thirdly, the internal structural characteristics of natural frequencies, normalized frequencies and frequency change ratios are studied. And then the condition feature vector for CIFS is extracted by use of the vibration measurements. Finally, the validity of the proposed approach is evaluated by a case study. The results demonstrate that the proposed approach can effectively identify each condition of free span when condition variation occurs even if under measurement noise. It is concluded that the proposed method is a promising tool for CIFS in real applications.