The diagnosis and treatment of functional movement disorders are challenging for clinicians who manage patients with movement disorders. The borderline between functional and organic dystonia is often ambiguous. Patients with functional dystonia are poor responders to pallidal deep brain stimulation (DBS) and are not good candidates for DBS surgery. Thus, if patients with medically refractory dystonia have functional features, they are usually left untreated with DBS surgery.  https://www.selleckchem.com/HIF.html  In order to investigate the outcome of functional dystonia in response to pallidal DBS surgery, we retrospectively included five patients with this condition. Their dystonia was diagnosed as organic by dystonia specialists and also as functional according to the Fahn and Williams criteria or the Gupta and Lang Proposed Revisions. Microelectrode recordings in the globus pallidus internus of all patients showed a cell-firing pattern of bursting with interburst intervals, which is considered typical of organic dystonia. Although their clinical course after DBS surgery was incongruent to organic dystonia, the outcome was good. Our results question the possibility to clearly differentiate functional dystonia from organic dystonia. We hypothesized that functional dystonia can coexist with organic dystonia, and that medically intractable dystonia with combined functional and organic features can be successfully treated by DBS surgery.In order to study the deterioration and mechanism of dry-wet cycles and sulfate attack on the performance of concrete in seaside and saline areas, the deterioration of compressive strength of concrete with different water cement ratios under different erosion environments (sodium sulfate soaking at room temperature and coupling of dry-wet cycling and sodium sulfate) was studied here. At the same time, ICT (industrial computed tomography) and NMR (nuclear magnetic resonance) techniques were used to analyze the internal pore structure of concrete under different erosion environments. The results show that the compressive strength under different erosion environments increases first and then decreases, and the dry-wet cycle accelerates the sulfate erosion. With the increase of dry and wet cycles, larger pores are filled with erosion products and developed into small pores in the early stage of erosion; in the later stage of erosion, the proportion of larger pores increases, and cracks occur inside the sample. In the process of sulfate soaking and erosion, the smaller pores in the concrete account for the majority. As the sulfate erosion continues, the T2 spectrum distribution curve gradually moves right, and the signal intensity of the larger pores increases.Background and Objectives Late preterm (LP) infants (born between 34 and 36 weeks of gestational age) are considered at higher risk of neonatal morbidities, mortality, and neurological impairments than full-term born infants (FT). The aim of this study was to provide a critical review of the literature outlining the different aspects of neurological function reported both in the neonatal period and in the follow up of late preterm infants. Materials and Methods A comprehensive search of the MEDLINE, Embase, PsycINFO, and CINAHL electronic databases was made, using the following search terms 'Late preterm infants', 'Near term infants', 'neurological assessment', 'neurological outcome', 'neuromotor outcome', cerebral palsy', 'CP', 'motor impairment', including all the studies reporting clinical neurological assessment of LP (including both neonatal period and subsequent ages). Results A total of 35 articles, comprising 301,495 children, were included as fulfilling the inclusion criteria ten reported neonatal neurological findings, seven reported data about the first two years after birth, eighteen reported data about incidence of CP and motor disorder during the infancy. Results showed a more immature neurological profile, explored with structured neurological assessments, in LP infants compared with FT infants. The LP population also had a higher risk of developing cerebral palsy, motor delay, and coordination disorder. Conclusion LP had a higher risk of neurological impairments than FT infants, due to a brain immaturity and an increased vulnerability to injury, as the last weeks of gestational age are crucial for the development of the brain.The lack of sentiment resources in poor resource languages poses challenges for the sentiment analysis in which machine learning is involved. Cross-lingual and semi-supervised learning approaches have been deployed to represent the most common ways that can overcome this issue. However, performance of the existing methods degrades due to the poor quality of translated resources, data sparseness and more specifically, language divergence. An integrated learning model that uses a semi-supervised and an ensembled model while utilizing the available sentiment resources to tackle language divergence related issues is proposed. Additionally, to reduce the impact of translation errors and handle instance selection problem, we propose a clustering-based bee-colony-sample selection method for the optimal selection of most distinguishing features representing the target data. To evaluate the proposed model, various experiments are conducted employing an English-Arabic cross-lingual data set. Simulations results demonstrate that the proposed model outperforms the baseline approaches in terms of classification performances. Furthermore, the statistical outcomes indicate the advantages of the proposed training data sampling and target-based feature selection to reduce the negative effect of translation errors. These results highlight the fact that the proposed approach achieves a performance that is close to in-language supervised models.Language-based person search retrieves images of a target person using natural language description and is a challenging fine-grained cross-modal retrieval task. A novel hybrid attention network is proposed for the task. The network includes the following three aspects First, a cubic attention mechanism for person image, which combines cross-layer spatial attention and channel attention. It can fully excavate both important midlevel details and key high-level semantics to obtain better discriminative fine-grained feature representation of a person image. Second, a text attention network for language description, which is based on bidirectional LSTM (BiLSTM) and self-attention mechanism. It can better learn the bidirectional semantic dependency and capture the key words of sentences, so as to extract the context information and key semantic features of the language description more effectively and accurately. Third, a cross-modal attention mechanism and a joint loss function for cross-modal learning, which can pay more attention to the relevant parts between text and image features.