Boosting Photocatalytic Efficiency of MoS2/CdS By Modulating Morphology

With the rapid development of nuclear-related industries in the world, the consequent environmental pollution of radionuclides has become an increasingly serious problem due to the great harm to environmental diversity and human health. The photocatalytic removal of radionuclide on CdS-based photocatalysts has been attracted widely attentions due to the suitable band gap and high photocatalytic efficiency. In this study, approximately 97.5% of U(VI) was photo-catalytically reduced into U(IV) by 2.5 wt% MoS2/CdS composite within 15 min. After 5 cycles, 2.5 wt% MoS2/CdS composite still exhibited the high removal efficiency of U(VI) under 50 min irradiation, indicating the good stability. The findings indicated that CdS-based catalyst has a great potential for the photocatalytic reduction of uranyl in actual environmental remediation.

Research on Parameter Optimization Based on Genetic Algorithm to Suppress Transient Overvoltage of LCC-HVDC System

Since the 1980s, the direct current (DC) transmission technology has developed rapidly in China. However, with the large-scale application of DC transmission technology, new problems are brought to the power system. Commutation failure of the DC system will cause overvoltage in the alternating current (AC) power network, which will cause great harm to the weak AC system with wind power access. Therefore, it is urgent to carry out research on overvoltage suppression at the sending end of AC system. This paper reveals the formation mechanism of transient overvoltage and confirms that the control parameters of DC system influence the voltage at the sending end directly. And the appropriate control parameters were selected to suppress the overvoltage by the parameter optimization based on genetic algorithm (GA).

Anchor voiceprint recognition in live streaming via RawNet-SA and gated recurrent unit

With the sharp booming of online live streaming platforms, some anchors seek profits and accumulate popularity by mixing inappropriate content into live programs. After being blacklisted, these anchors even forged their identities to change the platform to continue live, causing great harm to the network environment. Therefore, we propose an anchor voiceprint recognition in live streaming via RawNet-SA and gated recurrent unit (GRU) for anchor identification of live platform. First, the speech of the anchor is extracted from the live streaming by using voice activation detection (VAD) and speech separation. Then, the feature sequence of anchor voiceprint is generated from the speech waveform with the self-attention network RawNet-SA. Finally, the feature sequence of anchor voiceprint is aggregated by GRU to transform into a deep voiceprint feature vector for anchor recognition. Experiments are conducted on the VoxCeleb, CN-Celeb, and MUSAN dataset, and the competitive results demonstrate that our method can effectively recognize the anchor voiceprint in video streaming.

Beyond the List: Bioagent-Agnostic Signatures Could Enable a More Flexible and Resilient Biodefense Posture Than an Approach Based on Priority Agent Lists Alone

As of 2021, the biothreat policy and research communities organize their efforts around lists of priority agents, which elides consideration of novel pathogens and biotoxins. For example, the Select Agents and Toxins list is composed of agents that historic biological warfare programs had weaponized or that have previously caused great harm during natural outbreaks. Similarly, lists of priority agents promulgated by the World Health Organization and the National Institute of Allergy and Infectious Diseases are composed of previously known pathogens and biotoxins. To fill this gap, we argue that the research/scientific and biodefense/biosecurity communities should categorize agents based on how they impact their hosts to augment current list-based paradigms. Specifically, we propose integrating the results of multi-omics studies to identify bioagent-agnostic signatures (BASs) of disease—namely, patterns of biomarkers that accurately and reproducibly predict the impacts of infection or intoxication without prior knowledge of the causative agent. Here, we highlight three pathways that investigators might exploit as sources of signals to construct BASs and their applicability to this framework. The research community will need to forge robust interdisciplinary teams to surmount substantial experimental, technical, and data analytic challenges that stand in the way of our long-term vision. However, if successful, our functionality-based BAS model could present a means to more effectively surveil for and treat known and novel agents alike.

The Fate Status of Stem Cells in Diabetes and its Role in the Occurrence of Diabetic Complications

Diabetes mellitus (DM) is becoming a growing risk factor for public health worldwide. It is a very common disease and is widely known for its susceptibility to multiple complications which do great harm to the life and health of patients, some even lead to death. To date, there are many mechanisms for the complications of diabetes, including the generation of reactive oxygen species (ROS) and the abnormal changes of gas transmitters, which ultimately lead to injuries of cells, tissues and organs. Normally, even if injured, the body can quickly repair and maintain its homeostasis. This is closely associated with the repair and regeneration ability of stem cells. However, many studies have demonstrated that stem cells happen to be damaged under DM, which may be a nonnegligible factor in the occurrence and progression of diabetic complications. Therefore, this review summarizes how diabetes causes the corresponding complications by affecting stem cells from two aspects: stem cells dysfunctions and stem cells quantity alteration. In addition, since mesenchymal stem cells (MSCs), especially bone marrow mesenchymal stem cells (BMMSCs), have the advantages of strong differentiation ability, large quantity and wide application, we mainly focus on the impact of diabetes on them. The review also puts forward the basis of using exogenous stem cells to treat diabetic complications. It is hoped that through this review, researchers can have a clearer understanding of the roles of stem cells in diabetic complications, thus promoting the process of using stem cells to treat diabetic complications.

Nursing actions in primary care in view of the risks of hypertension during pregnancy

Preeclampsia presents itself as one of the hypertensive syndromes that can affect women during pregnancy, during childbirth and/or in the postpartum period up to 10 days, so that it is still a pathology that, when not properly diagnosed and treated, can cause great harm and even lead to the death of the pregnant woman and/or parturient. The main objective of this study is to know the prevention of preeclampsia in primary care by nursing. Therefore, the following question is: what are the nursing actions in Primary Care in the face of the risks of hypertension during pregnancy? The present work is based on a bibliographic research, with a qualitative approach carried out through the integrative review method. To collect the data, an investigation was carried out in the databases: Google Scholar, Pubmed, Scielo and Medline. The descriptors used were: Risks. Gestation. Hypertension. Nursing. The inclusion criteria used for sample selection were: articles available electronically published from 2015 to 2020; language Portuguese. Exclusion criteria were articles lower than 2015 and keywords that are not related to the theme. For the full analysis of the selected articles, an online platform (search in databases) was used, with the purpose of extracting (title and purpose of the articles), organizing (in table form), summarizing the information and facilitating the formation of the database. The results indicated 35 published articles, but only 15 articles, in the last five years, have as main theme the prevention and risks of preeclampsia in primary care. It is concluded that the main conducts used not only by nurses, but by the entire team working in primary care, should be based on the welcoming process focused on actions that may be determinant in the prevention of preeclampsia.

Research Progress on Oil Sludge Treatment in Oilfield: A Mini-Review

: A large amount of sludge produced in the processing of crude oil has brought great harm. In this paper, common flocculants are summarized. According to the treatment process of crude oil, flocculants are divided into organic flocculants, inorganic flocculants, microbial flocculants, composite flocculants, and magnetic flocculants. The mechanism and limitation of each flocculation on crude oil sludge were analyzed. Finally, it is pointed out that the flocculation process of sludge is complex, and the development of new flocculant with high efficiency, safety, and economy is the main trend of flocculant development in the future.

Exploring the potential of herbal drugs for the treatment of hair loss

Hair loss can be recognized as a life-threatening disorder. It is a health condition during which hair is lost from some or all areas of the body, usually from the scalp. However, it has a great harm to a person’s self-respect, mental health, and entirety quality of life. Balding can be caused because of various reasons, like genetic tendencies, environmental triggers, exposure to chemicals, medicines, nutritional deficiency, extreme stress or long illness etc. In present article, we have covered information about loss of hair loss, types of alopecia, causes and various medicinal plants and parts they’re of used in treatment prophylaxis or treatment of hair loss.

DebtG: A Graph Model for Debt Relationship

Debt is common in daily transactions, but it may bring great harm to individuals, enterprises, and society and even lead to a debt crisis. This paper proposes a weighted directed multi-arc graph model DebtG of debts among a large number of entities, including individuals, enterprises, banks, and governments, etc. Both vertices and arcs of DebtG have attributes. In further, it defines three basic debt structures: debt path, debt tree, and debt circuit, and it presents algorithms to detect them and basic methods to solve debt clearing problems using these structures. Because the data collection and computation need a third-party platform, this paper also presents the profit analysis of the platform. It carries out a case analysis using the real-life data of enterprises in Huangdao Zone. Finally, it points out four key problems that should be addressed in the future.

Abandoned Object Detection

In the current fast paced life, security has become an important aspect which cannot be ignored. One of the usually neglected but important division of security in public areas involves the unattended objects. Bombs and other harmful objects that are incendiary cause great harm. And in most of the cases such objects are left unattended for some time before causing harm. As such, unattended objects should be given importance and must be checked to ensure safety. This paper shows a method to identify unattended objects in public areas. This is done by comparing a fixed/initial background frame with frames after a fixed interval. If there is a change in the frames, then that refers to an attended object. No change observed, proves an unattended object which is highlighted by a box. This is done with the help of blob analysis. This paper does this with the help of MATLAB. MATLAB being a software accessible to wide range of people provides an easy process with moderate results. It uses a wide range of predefined functions and toolboxes to do this.