Objective: To describe outcomes of patients with coronavirus disease 2019 (COVID-19) in the outpatient setting after early treatment with zinc, low dose hydroxychloroquine, and azithromycin (the triple therapy) dependent on risk stratification. Design: Retrospective case series study. Setting: General practice. Participants: 141 COVID-19 patients with laboratory confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in the year 2020. Main Outcome Measures: Risk-stratified treatment decision, rate of hospitalization and all-cause death. Results: Of 335 positively PCR-tested COVID-19 patients, 127 were treated with the triple therapy. 104 of 127 met the defined risk stratification criteria and were included in the analysis. In addition, 37 treated and eligible patients who were confirmed by IgG tests were included in the treatment group (total N=141). 208 of the 335 patients did not meet the risk stratification criteria and were not treated. After 4 days (median, IQR 3-6, available for N=66/141) of onset of symptoms, 141 patients (median age 58 years, IQR 40-67; 73% male) got a prescription for the triple therapy for 5 days. Independent public reference data from 377 confirmed COVID-19 patients of the same community were used as untreated control. 4 of 141 treated patients (2.8%) were hospitalized, which was significantly less (p<0.001) compared with 58 of 377 untreated patients (15.4%) (odds ratio 0.16, 95% CI 0.06-0.5). Therefore, the odds of hospitalization of treated patients were 84% less than in the untreated group. One patient (0.7%) died in the treatment group versus 13 patients (3.5%) in the untreated group (odds ratio 0.2, 95% CI 0.03-1.5; p=0.16). There were no cardiac side effects. Conclusions: Risk stratification-based treatment of COVID-19 outpatients as early as possible after symptom onset with the used triple therapy, including the combination of zinc with low dose hydroxychloroquine, was associated with significantly less hospitalizations and 5 times less all-cause deaths.

The world is in the grips of the COVID-19 pandemic. Public health measures that can reduce the risk of infection and death in addition to quarantines are desperately needed. This article reviews the roles of vitamin D in reducing risk of respiratory tract infections, knowledge about the epidemiology of influenza and COVID-19, and how vitamin D supplementation might be a useful measure to reduce risk. Through several mechanisms, vitamin D can reduce risk of infections. Those mechanisms include inducing cathelicidins and defensins that can lower viral replication rates and reducing concentrations of pro-inflammatory cytokines that produce the inflammation that injures the lining of the lungs, leading to pneumonia, as well as increase concentrations of anti-inflammatory cytokines. Several observational studies and clinical trials reported that vitamin D supplementation reduced risk of influenza, whereas others did not. Evidence supporting the role of vitamin D in reducing risk of COVID-19 includes that the outbreak occurred in winter, a time when 25-hydroxyvitamin D [25(OH)D] concentrations are lowest; that the number of cases in the Southern Hemisphere near the end of summer are low; that vitamin D deficiency has been found to contribute to acute respiratory distress syndrome, and that case-fatality rates increase with age and with chronic disease comorbidity, both of which are associated with lower 25(OH)D concentration. To reduce risk of infection, it is recommended that people at risk of influenza and/or COVID-19 consider taking 10,000 IU/d of vitamin D₃ for a few weeks to rapidly raise 25(OH)D concentrations, followed by 5000 IU/d. The goal should be to raise 25(OH)D concentrations above 40–60 ng/ml (100–150 nmol/l). For treatment of people who become infected with COVID-19, higher vitamin D₃ doses might be useful. Randomized controlled trials and large population studies should be conducted to evaluate these recommendations.

COVID-19 pandemic has affected the public educational sectors in terms of adjustment in educational modalities of instructional delivery, school operations, and policies. With this emerging paradigm shift, teachers' crisis self-efficacy and work commitment are relevant for research. This study's main objective was to determine the significant influence of crisis self-efficacy on the work commitment of public school teachers in Region XI (Davao Region), Philippines, during the COVID-19 pandemic. The sample consisted of 1,340 public school teachers across the Davao Region. The researchers collected the data through adapted questionnaires contextualized to the local setting and administered through online Google forms with appended consent. Mean, standard deviation, Pearson r, and regression analysis were used to analyze data. Results revealed that crisis self-efficacy significantly influences the work commitment of public school teachers during the COVID-19 pandemic. Uncertainty management during this crisis, in particular, best predicts teachers’ work commitment. Data also showed a high level of crisis self-efficacy in terms of action, preventive, achievement and uncertainty management, and high level of teachers’ work commitment in terms of commitment to school, commitment to students, commitment to teaching, and commitment to profession. Correlation results also showed a link between crisis self-efficacy and the work commitment of teachers amid pandemic. Finally, the study concluded with practical recommendations and directions for future research.

Background: Although no specific treatment for COVID 19 has been proven effective yet, some drugs with in vitro potential against SARS-CoV-2 virus have been proposed for clinical use. Hydroxychloroquine has in vitro anti-viral and immunomodulatory activity, but there is no current clinical evidence of its effectiveness on the outcome of the disease. Methods: We enrolled all 18-85 years old inpatients from Central Defense Hospital, Madrid, Spain, who were hospitalised due to COVID-19 and had a definitive outcome (either dead or discharged). We used a statistical survival analysis. Results: We analysed 220 medical records. 166 patients met the inclusion criteria. 48,8 % of patients not treated with HCQ died, versus 22% in the group of hydroxychloroquine (p=0,002). According to clinical picture at admission, hydroxychloroquine increased the mean cumulative survival in all groups from 1,4 to 1,8 times. This difference was statistically significant in the mild group. Conclusions: in a cohort of 166 patients between 18 to 85 years hospitalised with COVID-19, hydroxychloroquine treatment with an initial loading dose of 800mg improved patient survival when admitted in early stages of the disease. There was a non-statistically significant trend towards survival in all groups, which will need to be clarified in subsequent studies.

Imaging lidars are one of the hottest topics in the optronics industry. The need to sense the surroundings of every autonomous vehicle has pushed forward a career to decide the final solution to be implemented. The diversity of state-of-the art approaches to the solution brings, however, a large uncertainty towards such decision. This results often in contradictory claims from different manufacturers and developers. Within this paper we intend to provide an introductory overview of the technology linked to imaging lidars for autonomous vehicles. We start with the main single-point measurement principles, and then present the different imaging strategies implemented 8 in the different solutions. An overview of the main components most frequently used in practice is also presented. Finally, a brief section on pending issues for lidar development has been included, 10 in order to discuss some of the problems which still need to be solved before an efficient final implementation.Beyond this introduction, the reader is provided with a detailed bibliography containing both relevant books and state of the art papers.

This review will explore the four major pillars required for design and development of an saRNA vaccine: antigen design, vector design, non-viral delivery systems, and manufacturing (both saRNA and lipid nanoparticles (LNP)). In will report on the major innovations, preclinical and clinical data reported in the last five years and will discuss future prospects.

Background: On Dec 19, 2019, the public health department of China reported that an outbreak of pneumonia was caused by a novel Coronavirus. The virulence of the new virus COVID-19 was much greater than either the SARs and MERSs viruses and on March 11, 2020, the World Health Department (WHO) declared a worldwide pandemic. Understanding the pathophysiology of virulence of the SARS-COV-2 virus is absolutely necessary for understanding the transmission, virulence factors, reduce risk factors, clinical presentation, predict outcomes of the disease and provide guidance for any current or future treatment protocols. Methodology: A comprehensive PubMed search was performed during December 20, 2019 and April 03, 2020, utilizing the words: Wuhan Virus, COVID-19, SARs coronavirus, ACE2, S-protein, virulence, clinical presentation, epidemiology, genome, treatment, structure, MERs, pathogenesis and/or pathology alone and in combination with other terms. Each paper was evaluated by three content experts for quality, reproducibility, credibility and reputation of the journal. Results: The SARS-COV-2 virus is much more virulent than either the SAR’s or MER’s virus and its ability to cause serious disease inversely corresponds to the person’s ability to produce T-cells which declines linearly with age. The ACE2 receptor binding site does not vary among different ethnic groups but do in ACE-2 expression levels. This variance in expression level may explain for different infectivity rates among men and women and predict and explain different susceptibilities to infection by different ethnic groups. Furthermore, by understanding the underlying pathophysiology one can explain and provide guidance to the clinical effectiveness of any treatment. Conclusions: The underlying pathophysiology of COVID-19 explains not only the virulence, and clinical presentation, but, explains at a molecular level the comorbidity risk factors such as hypertension, sex, and age. Ethnic and anatomic expression patterns of ACE-2 and associated pathophysiology suggests that Native Americans and Asians may be particularly susceptible to this disease.

Proteins possess complex three-dimensional structures, and these structures are stable only within specific ranges of temperature which mostly correspond to the temperature ranges of the host organisms. However, few exceptional proteins, called heat-stable proteins, are stable at temperatures that are substantially higher than those tolerated by the host organisms themselves. Most of the heat-stable proteins possess heat stability to perform their functions at high temperatures, but some of them are intrinsically heat-stable due to their structure. Heat-stable proteins are usually divided into three or four groups depending upon the intricacies of their structures and thermal behaviors. Their peculiar property, i.e. heat-stability, makes them very valuable in applications such as polymerase chain reaction, industrial processes requiring high temperature, and protein engineering. Heat-stability also makes it feasible to purify such proteins, from the rest of the heat-labile proteins, using a simple heat-treatment method. Moreover, heat treatment can be used as a combined cell-lysis and protein purification step which, as compared to conventional methods, can result in a higher yield of heat-stable proteins. Furthermore, some special heat-stable proteins, i.e. intrinsically disordered proteins (which include the proteins involved in important neurodegenerative diseases), need heat-treatment step, in some cases, as the only way for their successful purification and study. Hence, this paper provides a first-ever comprehensive review of all major aspects of heat-stable proteins, i.e., their structure, evolution, classification, significance, and heat-treatment mediated purification.

Background: The incidences of COVID-19 related suicide among adolescents and youths have been reported across the world. There is no cumulative study focusing on nature, patterns, and causative factors that lead to the present investigation. Methods: A purposive sampling of google news between 15 February to 6 July was performed. After excluding duplicate reports, the final list comprised a total of 37-suicide cases across 11 countries. Results: More male suicides were reported (21-cases, i.e., 56.76%), and the mean age of the total victims was 16.6±2.7 years (out of a total of 29-cases). About two-thirds of the suicides were from three countries named India (11-cases), United Kingdom (8-cases), and the USA (6-cases). Out of 23-student victims, 14 were school-going students. Hanging was the most common suicide method accounting in 51.4% of cases. The most common suicide causalities were related to mental sufferings such as depression, loneliness, psychological distress, etc., whereas either online schooling or overwhelming academic distress was placed as the second most risk factors followed by TikTok addiction-related psychological distress, and tested with COVID-19. Conclusion: The finding of the temporal distribution of suicides concerning lockdowns may help in exploring and evolving public measures to prevent/decrease pandemic-related suicides in young people.

The fatigue strength of the hot work steel depends on various factors, including the mechanical, properties and behavior and bulk and the surface under layer, the microstructural features as well as heat treatments. The influence of a series of heat treatments on the fatigue strength of H13 hot work steel was investigated. Different preheating, quenching and tempering treatments were applied to four sets of specimens and fatigue tests were conducted at room temperature using a rotating bending test machine. All heat treatments resulted in a certain improvement of the fatigue strength. Highest fatigue strength obtained by applying a double tempering heat treatment (first tempering at 550 °C for two hours and second tempering at 610 °C for two hours) after initial preheating and quenching. One tempering treatment (550 °C for two hours after preheating and quenching) did not significantly improve the fatigue strength.

The market for autonomous vehicles (AV) is expected to experience significant growth over the coming decades and to revolutionize the future of transportation and mobility. The AV is a vehicle that is capable of perceiving its environment and perform driving tasks safely and efficiently with little or no human intervention and is anticipated to eventually replace conventional vehicles. Self-driving vehicles employ various sensors to sense and perceive their surroundings and, also rely on advances in 5G communication technology to achieve this objective. Sensors are fundamental to the perception of surroundings and the development of sensor technologies associated with AVs has advanced at a significant pace in recent years. Despite remarkable advancements, sensors can still fail to operate as required, due to for example, hardware defects, noise and environment conditions. Hence, it is not desirable to rely on a single sensor for any autonomous driving task. The practical approaches shown in recent research is to incorporate multiple, complementary sensors to overcome the shortcomings of individual sensors operating independently. This article reviews the technical performance and capabilities of sensors applicable to autonomous vehicles, mainly focusing on vision cameras, LiDAR and Radar sensors. The review also considers the compatibility of sensors with various software systems enabling the multi-sensor fusion approach for obstacle detection. This review article concludes by highlighting some of the challenges and possible future research directions.

In 2015, the Self-Action Leadership Theory—a qualitative, nomological expansion of self-leadership theory rooted in atmospheric and astronomical metaphor aimed at expanding the personal freedom of individuals, organizations, and nations by bolstering the existential growth of individuals through a series of Maslow-esque stages of holistic, personal development. This article introduces an accompanying, practitioner-based Model of Self-Action Leadership (SAL) aimed at the implicit enhancement of a holistic range of administrative processes through explicit training, mentoring, and coaching in the model’s general and universally-applicable principles and practices. The SAL model produces an original construct of personal leadership practice that builds upon the extant self-leadership academic canon, which dates back to 1983 (Manz, 1983). It also provides an analogue to four of the five core processes of Project Management by positioning a self-action leader (an individual) as the ongoing “project” at hand. The SAL Model is rooted in action research and was developed through a variety of self-oriented, action research projects in conjunction with a comprehensive, qualitative, analytical autoethnographic study of a scholar’s life experiences.

We are proposing, for any interested investigator, a randomized open clinical trial for mild and mild-to-moderate Covid-19 comparing a treatment regimen with standard of care, and eventually with another investigational regimen, if ongoing or will be implemented. The patients could be hospitalized or ambulatory but not requiring admission to intensive care units and mechanical ventilation. The proposed therapeutic regimen consists of doxycycline (an antimicrobial having also anti-inflammatory properties, probable antioxidant and possible some antiviral effects), and pentoxifylline, a hemorheological compound used in occlusive arterial diseases but also having proven anti-inflammatory properties. Doxycycline is included in the WHO’s list of essential medicine being an effective, safe, widely available, and inexpensive medication and widely accessible. It will be administered at a dosage of 100 mg orally twice daily for ten days. Pentoxifylline, in clinical use since 1972, and also widely accessible, will be given at a dosage of 400 mg orally, also twice daily, for ten days. The primary outcome measures are: 1) Progression of disease to a severe form requiring intensive care admission and mechanical ventilation; 2) Fatality rates and 3) Time to clinical recovery.This proposal was presented to the National Directors and Core Leads meeting of the Canadian Trials Network (CTN) on May 6, 2020. The interventional trial template suggested by CTN was used for designing the trial.

Studies in animal models have suggested that the ketogenic diet may be effective in the treatment of cancer. However, human cohort studies on the ketogenic diet have, thus far, failed to show benefits in cancer survival or in any other hard clinical endpoints of the disease. This paper presents a case report of a patient with glioblastoma multiforme. The patient had initially been treated with standard oncotherapy including surgery, radiotherapy and chemotherapy. Despite standard treatment, the patient experienced a recurrence of the glioblastoma seven months later. Subsequently, the patient refused radiotherapy and chemotherapy and opted to use the paleolithic ketogenic diet (PKD) as a stand-alone therapy. Following the adoption of the PKD, progression of the disease has been completely halted. At the time of writing, the patient has remained in remission for 48 months, is without side-effects and experiences an excellent quality of life without the use of any drugs.

Endocrine disrupting compounds (EDCs) are contaminants with estrogenic or androgenic activity that negatively impact human and animal communities. These compounds have become one of the significant concerns for wastewater treatment in recent decades. Several studies have evaluated EDC removal methods from wastewater across the globe including the United Kingdom (UK). Accordingly, the current study reviews EDC removal methods from municipal/domestic wastewater in the United Kingdom (UK) for the period of 2010–2017. The research highlights that despite the relative efficacy of existing chemical and physical methods for removing certain EDCs from wastewater there is emerging evidence supporting the need for more widespread application of nature-based and biological approaches, particularly the use of biofilms. The analysis reveals that there have been relatively few research studies on EDC removal methods have been carried out in the UK in the 2010–2017 period and none of the research focused on EDC removal using biofilms. Finally, this review suggests that more research is needed to remove EDCs, particularly through the application of biofilms, from municipal wastewater in current scenarios.

This article will examine the ambivalence in the views of Jewish authorities towards suicide. There are Jewish rulings which forbid the taking of one's own life, including requested euthanasia. There are seemingly contrary rulings which tolerate and sometimes admire suicide, particularly under conditions of religious persecution. The article will attempt an overview of suicide rates in Jewish communities, indicating variations in different circumstances. The question of whether religiosity affects suicide will be raised and examined. These variations—and of course other factors—may offer some clues to the precursors of suicide, and the processes which may be involved. The causal and risk factors in self-harm among Jews will also be examined. The article then turns to post-suicide events, behaviours and attitudes in Jewish communities.

ASTM A743 CA6NM alloy is a martensitic stainless steel typically used in energy industry -runners and hydraulic turbine components- due to its superior toughness, yield and fatigue properties. In both the manufacturing, shielded metal arc welding is applied to join for this grade steels. However, weldability of the steels is limited due to formation of hard and brittle phases such as untempered martensite during welding and post weld heat treatment processes. The formation causes a reduction in toughness. In this study, influence of post-weld heat treatment procedure (single tempering and double tempering) and parameters on microstructure and hardness of AWS410NiMo all weld metal. Hardness tests were conducted from weld metal. Microstructures of the all weld metals subjected to different heat treatment process were characterized.

The abundant mechanical vibration energy in bridge road environment can be converted into electric energy by using the piezoelectric energy harvest technology, which could be an efficient way to provide energy required by the wireless sensor network in the bridge condition monitoring system. An autonomous energy harvesting system has been designed based on cantilever beams for sensing and acquiring the bridge vibration energy. After the analysis of the dynamic properties of the piezoelectric cantilever beam in the energy conversion, three kinds of interface circuits were compared through simulation and experimental results. It was shown that the VD interface circuit has less power loss. Furthermore, the proposed closed loop control method based on the VD circuit was simple, adaptive, and self-powered, which is suitable for the road energy harvesting application. Finally, the energy harvesting system based on VD circuit was realized with harvested power of around 0.8mW.

Since the first generation of 7xxx superhard aluminum alloy was investigated in 1930, hitherto the fifth generation aluminum alloy materials with high comprehensive properties such as high static strength, high strength, heat resistance, high toughness, damage resistance, low density and low quenching sensitivity have been improved and developed. This paper reviews the progress of 7xxx aluminum alloy materials in composition, microstructure, properties, preparation methods, heat treatment strengthening and applications from 2014 to 2021. The effect of adding trace elements on microstructure and properties of 7xxx series alloy and the problems existing in aging precipitation characteristics and reinforcement mechanism are discussed. The future development direction of 7xxx superhard aluminum alloy is prospected by optimizing heat treatment technological, adding appropriate trace elements to alloy and controlling alloy microstructure.

Thin film transistors (TFTs) using In-Ga-Zn Oxide (IGZO) as active layer and the gate insulator was treated with NH3 plasma and N2O plasma, respectively, which is fabricated on flexible PI substrate in this work. The performance of IGZO TFTs with different plasma species and treatment time are investigated and compared. The experiment results show that the plasma species and treatment time play an important role in the threshold voltage, field-effect mobility, Ion/Ioff ratio, sub-threshold swing (SS) and bias stress stability of the devices. The TFT with a 10 seconds NH3 plasma treatment shows the best performance; specifically, threshold voltage of 0.34 V, field-effect mobility of 15.97 cm2/Vs, Ion/Ioff ratio of 6.33×107, and sub-threshold swing of 0.36 V/dec. The proposed flexible IGZO-TFTs in this paper can be used as driving devices in the next-generation flexible displays.

In the era when the market segment of Internet of Things (IoT) tops the chart in various business reports, it is apparently envisioned that the field of medicine expects to gain a large benefit from the explosion of wearables and internet-connected sensors that surround us to acquire and communicate unprecedented data on symptoms, medication, food intake, and daily-life activities impacting one’s health and wellness. However, IoT-driven healthcare would have to overcome many barriers, such as: 1) There is an increasing demand for data storage on cloud servers where the analysis of the medical big data becomes increasingly complex; 2) The data, when communicated, are vulnerable to security and privacy issues; 3) The communication of the continuously collected data is not only costly but also energy hungry; 4) Operating and maintaining the sensors directly from the cloud servers are non-trial tasks.This book chapter defined Fog Computing in the context of medical IoT. Conceptually, Fog Computing is a serviceoriented intermediate layer in IoT, providing the interfaces between the sensors and cloud servers for facilitating connectivity, data transfer, and queryable local database. The centerpiece of Fog computing is a low-power, intelligent, wireless, embedded computing node that carries out signal conditioning and data analytics on raw data collected from wearables or other medical sensors and offers efficient means to serve telehealth interventions. We implemented and tested an fog computing system using the Intel Edison and Raspberry Pi that allows acquisition, computing, storage and communication of the various medical data such as pathological speech data of individuals with speech disorders, Phonocardiogram (PCG) signal for heart rate estimation, and Electrocardiogram (ECG)-based Q, R, S detection. The book chapter ends with experiments and results showing how fog computing could lessen the obstacles of existing cloud-driven medical IoT solutions and enhance the overall performance of the system in terms of computing intelligence, transmission, storage, configurable, and security. The case studies on various types of physiological data shows that the proposed Fog architecture could be used for signal enhancement, processing and analysis of various types of bio-signals.

Lyme disease and associated co-infections are increasing worldwide and approximately 20% of individuals develop chronic Lyme disease (CLD)/Post-Treatment Lyme Disease Syndrome (PTLDS) despite early antibiotics. A 7–8-week protocol of double dose dapsone combination therapy (DDDCT) for CLD/PTLDS results in symptom remission in approximately 50% of patients for one year or longer, with published culture studies indicating higher doses of dapsone demonstrate efficacy against resistant biofilm forms of Borrelia burgdorferi. The purpose of this study was therefore to evaluate higher doses of dapsone in the treatment of resistant CLD/PTLDS and associated co-infections. Twenty-five patients with a history of Lyme and associated co-infections, most of whom had ongoing symptoms despite several courses of DDDCT, took one or more courses of high dose pulsed dapsone combination therapy (200 mg dapsone X 3-4 days and/or 200 mg BID x 4 days), depending on persistent symptoms. The majority of patients noticed sustained improvement in 8 major Lyme symptoms, including fatigue, pain, headaches, neuropathy, insomnia, cognition, and sweating, where dapsone dosage, not just treatment length, positively affected outcomes. High dose pulsed dapsone combination therapy may represent a novel therapeutic approach for the treatment of resistant CLD/PTLDS, and should be confirmed in randomized, controlled clinical trials.

To better understand the shape memory materials and self-healing materials, a new series of liquid-crystalline shape memory polyurethane (LC-SMPU) composites, named SMPU-OOBAm, were successfully prepared by incorporating 4-octyldecyloxybenzoic acid (OOBA) into the PEG-based SMPU. The effect of OOBA on the structure, morphology and properties has been carefully investigated. The results demonstrate that SMPU-OOBAm have liquid crystalline properties, triple-shape memory properties and self-healing properties. The incorporated OOBA promotes the crystallizability of both soft and hard segments of SMPU, and the crystallization rate of the hard segment of SMPU decreases when the OOBA-content increases. Additionally, the SMPU-OOBAm forms a two-phase separated structure (SMPU phase and OOBA phase), and it shows two-step modulus changes upon heating. Therefore, the SMPU-OOBAm shows triple-shape memory behavior, and the shape recovery ratio decreases with an increase in the OOBA content. Finally, SMPU-OOBAm shows self-healing properties. The new mechanism can be ascribed to the heating-induced “bleeding” of OOBA in the liquid crystalline state and the subsequent re-crystallization upon cooling. This successful combination of liquid crystalline properties, triple-shape memory properties and self-healing properties make the SMPU-OOBAm composites with many promise applications in smart optical devices, smart electronic devices and smart sensors.

Abstract Background: Diabetes mellitus is dramatically increasing in the wide world. The managing of diabetes care emphasized the self-management education and support into patients’ care and family care. Objective: to review and synthesizes the effectiveness of DSME strategies involving family as a key person to provide social support for diabetes mellitus self-management of glycemic uncontrolled patients Method: Three databases through PubMed, CINAHL, and Scopus were reviewed to assess the relevant articles. The following search terms: “type 2 diabetes,” “self-management,” “family support,” and “glycemic uncontrolled.” We summarized details of family support on self-management among glycemic uncontrolled patients for 14 existing studies. Results: A total of 22 intervention studies were identified. Those studies have a heterogeneous of the education strategies, support perceived, follow-ups strategies and outcomes among type 2 DM. Family integration on diabetes self-management education (DSME) has a positive impact on several outcomes including, self-care behaviors, psychological outcomes, self-efficacy and clinical outcomes Conclusions: This systematic review found robust data related to the integration of family support on diabetes self-management among glycemic uncontrolled patients. Consequently, the improvement in outcomes was identified. Implications: The findings suggest model of family engagement is better and needed for sustaining the diabetes care in the long-term care

Proper management of water is a challenge for every individual but especially for companies. Nowadays also legislation obliges companies to clean the wastewater before being discharged into municipal public sewer especially if they use some chemicals or oily elements in their production process. Construction of the wastewater cleaner depends directly on the way of pollution, the amount of contaminated water and the energy demand of the cleaning process. The paper deals with the construction of the wastewater cleaner, which is based on the technology of electro-flotation for the treatment of water contaminated with disperse colorants. The experimental work as well as the modelling using the statistical methods proved the suitability of the chosen technology. Also, each colour combination requires a specific time period for the water treatment. The authors determined the time interval for cleaning the wastewater that was polluted with yellow colour to 33 minutes. Finally, the wastewater cleaner that is based on the electro-flotation technology was included in the company’s reverse logistics system.

In this study, a new type of temperature sensor device was developed. The circular electrode of the thermal sensitive sensor was modified with TMT and O₂ plasma to enhance the conductivity by forming a thin SnOxCy layer on the electrode surface. The Nano-Au particles were subjected to O₂ plasma pretreatment to form peroxide groups on the surface. The thermally sensitive sensor was made by mixing the above-treated Nano-Au particles with N-isopropylacrylamide (NIPAAm) to form solution and then UV-induced grafting polymerization of the NIPAAm-containing solution onto the electrode substrate. The composite hydrogels on the electrode introduce thermo-sensitive polymeric surface films for temperature sensing. Using ambient environment resistance test to measure the resistance, the LCST (lower critical solution temperature) of Nano-Au (MUA) mixed with NIPAAm hydrogel was found to be 32 °C. At ambient temperatures higher than LCST, the electrode resistance decreases linearly.

The Internet-of-Things (IoT) enables enterprises to obtain profits from data but triggers data protection questions and new types of cyber risk. Cyber risk regulations for the IoT however do not exist. The IoT risk is not included in the cyber security assessment standards, hence, often not visible to cyber security experts. This is concerning, because companies integrating IoT devices and services need to perform a self-assessment of its IoT cyber security posture. The outcome of such self-assessment needs to define a current and target state, prior to creating a transformation roadmap outlining tasks to achieve the stated target state. In this article, a comparative empirical analysis is performed of multiple cyber risk assessment approaches, to define a high-level potential target state for company integrating IoT devices and/or services. Defining a high-level potential target state represent is followed by a high-level transformation roadmap, describing how company can achieve their target state, based on their current state. The transformation roadmap is used to adapt IoT risk impact assessment with a Goal-Oriented Approach and the Internet of Things Micro Mart model.

Three patients with multi-year histories of relapsing and remitting Lyme disease and associated co-infections despite extended antibiotic therapy were each given double dose dapsone combination therapy (DDD CT) for a total of 7-8 weeks. At the completion of therapy, all three patients major Lyme symptoms remained in remission for a period of 25-30 months. In conclusion, Double dose dapsone therapy could represent a novel and effective anti-infective strategy in chronic Lyme disease/PTLDS, especially in those individuals who have failed regular dose dapsone combination therapy (DDS CT) or standard antibiotic protocols. A randomized, blinded, placebo-controlled trial is warranted to evaluate the efficacy of DDD CT in those individuals with chronic Lyme disease/PTLDS.

The betel nut chewing habit of taxi drivers has shown that can promote companionship, relaxation, and emotional stability at work. 19.3% of betel nut behaviors are instigated by an invitation among drivers to engage in the habit. The objective of this study was to explore the impact of social learning, subjective norm, and self-efficacy on betel nut chewing in taxi drivers in Taiwan. We conducted a cross-sectional study on taxis’ driver of betel nut behaviour and measured their evaluations of its consequences using a self-report questionnaire. Other variables include socio-demographic characteristics and chewing-related experience. The overall variance is 44.5% in socio-demographic variable, social learning, self-efficacy, and subjective norm. Results show that the variables of affected betel nut chewing behavior, driving years has the strongest influence, followed by learning about betel nut from the media, relatives, and friends, and education level, which positively affect betel nut chewing behavior. Findings indicated that education related to quitting betel nut chewing, significant others, and rules of the taxi fleet are adopted to design a plan for quitting betel chewing to reduce the positive expectations of taxi drivers for betel nut chewing and decrease their betel nut chewing behavior.

The present grievous situation of the tuberculosis disease can be improved by efficient case management and timely follow-up evaluations. With the advent of digital technology this can be achieved by quick summarization of the patient-centric data. The aim of our study was to assess the effectiveness of the ODK Scan paper-to-digital system during testing period of three months. A sequential, explanatory mixed-method research approach was employed to elucidate technology use. Training, smartphones, application and 3G enabled SIMs were provided to the four field workers. At the beginning, baseline measures of the data management aspects were recorded and compared with endline measures to see the impact of ODK Scan. Additionally, at the end, users’ feedback was collected regarding app usability, user interface design and workflow changes. 122 patients’ records were retrieved from the server and analysed for quality. It was found that ODK Scan recognized 99.2% of multiple choice bubble responses and 79.4% of numerical digit responses correctly. However, the overall quality of the digital data was decreased in comparison to manually entered data. Using ODK Scan, a significant time reduction is observed in data aggregation and data transfer activities, however, data verification and form filling activities took more time. Interviews revealed that field workers saw value in using ODK Scan, however, they were more concerned about the time consuming aspects of the use of ODK Scan. Therefore, it is concluded that minimal disturbance in the existing workflow, continuous feedback and value additions are the important considerations for the implementing organization to ensure technology adoption and workflow improvements.

This study explored the effects of cryogenic treatment on the microstructure, hardness, and wear-resistance of diamond-like carbon (DLC) by cryogenically treating NAK 80 mold steel coated with DLC. Raman spectroscopy analyzed the structure of the DLC film. Nanoindenter analyzed the hardness and Young’s modulus of the film, and their relationship determined the wear resistance. Wear test assessed the wear rate and friction coefficient of the DLC film. The results showed that cryogenic treatment increased the rate of carbide precipitation and refined the grain structure. Raman spectroscopy indicated that the Raman intensity rate (I_D/I_G) of treated DLC films was smaller than those without cryogenic treatment. When the sp3 bond increased, the hardness and wear-resistance of the DLC film also increased.

Development of the self-cleaning and anti-fogging superhydrophobic coating for aluminum surfaces which is durable in the aggressive conditions has raised tremendous interest in materials science. In this work, by employing chemical etching technique with mixture of hydrochloric and nitric acid, followed by passivation with lauric acid, superhydrophobic aluminum surface was synthesized. The surface morphology analysis reveals the presence of rough microstructures on coated aluminium surface. Superhydrophobicity with water contact angle of 170 ± 3.9° and sliding angle of 4 ± 0.5° is achieved. Surface bounces off the high speed water jet, indicating excellent water-repellent nature of coating. It is also continuously floated on water surface for several weeks, showing excellent buoyancy nature. Additionally, coating maintains its superhydrophobicity after undergoing 100 cycles of adhesive tape peeling test. Its superhydrophobic nature withstands 90° and 180° bending, and repeated folding and de-folding. Coating exhibits the excellent self-cleaning property. In low temperature condensation test, almost no accumulation of water drops on the surface, showing the excellent anti-fogging property of coating. This approach can be applied to any size and shape of aluminium surface and hence has great industrial applications.

We aimed to investigate the relationship between membrane material and development of membrane fouling in a membrane bioreactor (MBR) using membranes with different pore sizes and hydrophilicities. Batch filtration tests were performed using submerged single hollow fiber membrane ultrafiltration (UF) modules with different polymeric membrane materials including cellulose acetate (CA), polyethersulfone (PES), and polyvinylidene fluoride (PVDF) with activated sludge taken from a municipal wastewater treatment plant. The three UF hollow fiber membranes were prepared by a non-solvent-induced phase separation method and had similar water permeabilities and pore sizes. The results revealed that transmembrane pressure (TMP) increased more sharply for the hydrophobic PVDF membrane than for the hydrophilic CA membrane in batch filtration tests, even when membranes with similar permeabilities and pore sizes were used. PVDF hollow fiber membranes with smaller pores had greater fouling propensity than those with larger pores. In contrast, CA hollow fiber membranes showed good mitigation of membrane fouling regardless of pore size. The results obtained in this study suggest that the surface hydrophilicity and pore size of UF membranes clearly affect the fouling properties in MBR operation when using activated sludge.

Virus-infected Flu is a common disease. To date, no specific drugs are available to manage the symptoms of cough, headache and sputum production. An alternative Chinese herb medicine is introduced for virus-infected Flu or similar infection. Before hospitalization, some of patients may scare for cross-infection with mild symptoms or hardly go to hospital if encountered a temporary lockdown or quarantine. Some Chinese practice self-treatment of cough, headache and sputum production by inhalation of volatile chemicals from onion and garlic. Author used to take the same alternative approach of inhalation of onion, garlic or scallions for self-treatment when suffered virus caused flu with cough, headache and sputum production at onset disease. In this article, the biomedical effects of onion and garlic are reviewed. To help patients with mild symptoms of virus infected Flu, a simple home-based treatment was suggested to self-treatment because of temporary isolation and hardly going to hospitalization. The alternative approach may also suggest for some mild virus infected respiratory diseases caused by virus at onset disease.

Though Cyber Physical Systems (CPS) become very popular in last the decade, dependability of CPS is still a critical issue and related survey is rare. We try to spell out the jigsaw of technologies and figure out the technical trends of dependable self-managing CPS. This survey first recalls the motivation and the similar concepts. By analyzing four generic architectures, we summarize the common characteristics and related assurance technologies, and propose a more generic environment-in-loop processing flow of CPS and a formal interaction flow between physical space and cyber space. Further, the similarity between correctness and dependability is formally analyzed and the new five research questions of dependable self-managing CPS are presented. Then we review the critical technologies and related correctness verification & validation (V&V) methods, the architectures for dependable self-managing CPS. Further, the detail dependability management and V&V technologies are surveyed, which covers the areas of running-time fault management methods and whole life cycle V&V technologies, maintenance and available tool sets. For holistic CPS development, Modeling techniques and MDE (model driven engineering) based V&V methods are analyzed in detail. Then we complete the jigsaw of technologies and figure out the missing part. Further, we propose the technical challenges and the further direction. To our best knowledge, this is the first comprehensive survey on dependable self-managing CPS development and evaluation.

Owing to the nondiffracting, self-accelerating, and self-healing properties, Airy beams of different nature have become a subject of immense interest in the past decade. Their interesting properties have opened doors to many diverse applications. Consequently, the questions of how to properly design spatial manipulation of Airy beams or how to implement them in different setups have become important and timely in the development of various optical devices. Here, based on our previous work, we present a short review on the spatial control of Airy beams, including the interactions of Airy beams in nonlinear media, beam propagation in harmonic potential, and the dynamics of abruptly autofocusing Airy beams in the presence of a dynamic linear potential. We demonstrate that under the guidance of nonlinearity and external potential, the trajectory, acceleration, structure, and even the basic properties of Airy beams can be adjusted to suit specific needs. We describe other fascinating phenomena observed with Airy beams, such as self-Fourier transformation, periodic inversion of Airy beams, and the appearance of spatial solitons in the presence of nonlinearity. These results have promoted the development of Airy beams, and have been utilized in various applications, including particle manipulation, self-trapping, and electronic matter waves.

The advancement of bioconcrete over cementitious composites has brought us to the application of microbes in the field of construction materials. Certain microbes like bacteria, algae, and fungi have been discussed in the review. The purpose of applying these microbes in the matrix is mainly to enhance the concrete’s strength and other properties such as durability, resistance, and self-healing ability. As these microbes are able to induce calcite biomineralizations, the process is also known as Microbiologically Induced Calcite Precipitation (MICP). Some known microorganisms with their mentioned ability are Bacillus subtilis and Bacillus cohnii (bacteria), Chlorella vulgaris and Spirulina platensis (algae), and Trichoderma reesei, Aspergillus niger, and Neurospora crassa (fungi). The paper provides a “state-of-the-art” review of research into the effects of bioconcrete and discusses the overall methodologies of every medium with their physiological, physicochemical and bioengineering properties in the light of recent researches done so far in the same field.

Globally, an approximate of 380,000 patients succumbed to death due to the pandemic COVID-19 which also infected more than six million people since December 2019. Not sparing anyone, COVID-19 infections are widely reported among healthcare professionals, sanitation workers and researchers too while global leaders and various governments are providing their best in defending their citizens against this airborne and contact spread virus. In order to contain the virus and protect millions of lives from this deadly coronavirus, there is a need to have a combination of advanced engineering technology and medical facilities. Application of applied science, engineering and technology diffuse almost every aspect of contemporary living. Grasping the fundamentals to determine humanity's most imperative and forthcoming challenges is essential. Artificial Intelligence, the technology that learns, adapts and reciprocates the actions according to the situations, finds optimum position in the fight against corona virus and acts as a powerful tool against this pandemic. In this research article, the authors discusses how Artificial Intelligence (AI) can be leveraged to fight the deadly virus. The research paper further discusses the efficient utilization of AI across the globe to help in testing, treating and serving the population in these hard times. This manuscript focuses on the potential impact of the process in which AI can be implemented to prevent, test and treat.

COVID-19 has affected 212 countries around the world, killing nearly 300,000 and infecting more than 4.4 million by May 14, 2020. Bangladesh, a South Asian low-middle-income economy, has experienced a demographic and epidemiological transition with rapid urbanization and a gradual increase in life expectancy. It is the seventh most populous country in the world and population of the country is expected to be nearly double by 2050. The increasing burden of communicable diseases in Bangladesh can be attributable to rapid urbanization and nearly 50% of all slum dwellers of the country live in Dhaka division. In 2017, National Rapid Response Team of IEDCR investigated 26 incidents of disease outbreak. The joint survey of the Power and Participation Research Centre and BRAC Institute of Governance and Development reveals that per capita daily income of urban slum and rural poor drops by 80% due to present countrywide shutdown enforced by the government to halt the spread of Covid-19. 40%-50% of these population took loans to meet the daily expenses. However, the country has just 127,000 hospital beds, 91,000 of them in government-run hospitals. Researchers say, the country’s economy is economy is losing BDT 33 billion every day from its service and agriculture sectors during the nationwide shutdown.

There is increasing evidence and recognition that Lyme borreliosis, and other associated tick-borne diseases (LB/TBD) cause mental symptoms. Data was drawn from databases, search engines and clinical experience to review current information on LB/TBD. LB/TBD infections cause immune and metabolic effects that result in a gradually developing spectrum of neuropsychiatric symptoms, usually presenting with significant comorbidity and may include developmental disorders, autism spectrum disorders, schizoaffective disorders, bipolar disorder, depression, anxiety disorders (panic disorder, social anxiety disorder, generalized anxiety disorder, posttraumatic stress disorder, intrusive symptoms), eating disorders, decreased libido, sleep disorders, addiction, opioid addiction, cognitive impairments, dementia, seizure disorders, suicide, violence, anhedonia, depersonalization, dissociative episodes, derealization and other impairments. Screening assessment followed by a comprehensive psychiatric clinical exam relevant to patient’s complaints and findings with a thorough history, mental status exam, review of systems, neurological exam, physical exam, a knowledgeable interpretation of laboratory findings, pattern recognition and clinical judgment facilitate diagnosis. Psychotropics and antibiotics may help improve functioning and prevent further disease progression. Awareness of the association between LB/TBD and neuropsychiatric impairments and studies of their prevalence in neuropsychiatric conditions can improve understanding of the causes of mental illness and violence and result in more effective prevention, diagnosis and treatment.

Microbial electrochemical technologies (MET) rely on the presence of the metabolic activity of electroactive bacteria for the use of solid-state electrodes for oxidizing different kind of compound, that could lead to the synthesis of chemicals, bioremediation of polluted matrices, the treatment of contaminants of interest, as well as the recovery of energy. Keeping in mind those possibilities, since the beginning of the present century, there has been a growing interest in the use of electrochemical technologies for wastewater treatment, and if possible with simultaneous power generation. In the last years, there has been a growing interest to explore the possibility of merging MET with constructed wetlands, to offer a new option of intensified wetland system that could keep a high performance with a lower footprint. Based on that interest, this paper explains the general principles of MET, and the different known extracellular electron transfer mechanisms ruling the interaction between electroactive bacteria and potential solid-state electron acceptors. Also, the adoption of those principles for the development of MET set-ups for simultaneous wastewater treatment and power generation, and the challenges that the technology face. Ultimately, the most recent developments in set-ups that merges MET with constructed wetlands are presented and discussed.

Fluid flow in human body is generally known to influence a variety of cellular behaviors. Different nanoparticle properties as well as cell type, interaction with other cells and cellular environments also show significant effect on nanoparticle uptake and drug efficacy. The aim of this study was to evaluate the effect of shear stress on cellular behaviors of biocompatible and biodegradable nanoparticles to cancer cells (A549 cell lines) in a biomimetic microfluidic system. We prepared a gelatin-oleic conjugate (GOC) as an amphiphilic biomaterial to prepare self-assembled gelatin-oleic nanoparticles (GON). Coumarin-6 and paclitaxel were used as the fluorescence marker and model drug, respectively, and were loaded into GONs by incubation (C-GONs; PTX-GONs). Additionally, we evaluated the cellular uptake of fluorescence labeled C-GONs and the drug efficacy of PTX-GONs. The cellular uptake of C-GONs by A549 cells in the absence of shear stress revealed that the mean fluorescence intensity was slightly decreased compared to that in the presence of shear stress. The results also indicated that negatively charged PTX-GONs had a lower cancer killing effect under dynamic conditions than that under static conditions. It also suggested that fluidic shear stress did not significantly affect drug uptake and efficiency in case of PTX-GONs. The cellular interactions between nanoparticles and cells in drug delivery should be carefully examined according to the physicochemical properties of nanoparticles such as the type of materials, size and mainly surface charge in a biomimetic microfluidic condition.

The selection of biomaterials for biomedical application is a significant challenge. In the last few decades, various bioabsorbable and stable biopolymers have been applied for use as biomedical devices in orthopedic applications. Ultra-high molecular weight polyethylene (UHMWPE) has been extensively used in medical implants, notably in the bearings of hip, knee, and other joint prostheses, owing to its biocompatibility and high wear resistance. For the ACL graft, synthetic UHMWPE is an ideal candidate due to its biocompatibility and its extremely high tensile strength. Despite the appeal of new advanced materials such as carbon fiber, poly-ether-ether ketone, and other load-bearing materials, UHMWPE remains a primary load-bearing candidate material for ACL reconstructions because of its extremely high strength, the simplicity of the fabrication process, its biocompatibility, and low friction. However, some significant problems are observed in UHMWPE based implants, such as wear debris, and oxidative degradation due to the generation of free radicals when exposed to irradiation with gamma rays for grafting or sterilization. Various innovative methodologies have been developed to resolve those problems and enhance the properties of UHMWPE. In this review, we will explore in detail the methods for surface functionalization of UHMWPE and will apply these findings to the case study of UHMWPE for Anterior Cruciate Ligament repair.

Nowadays asymmetric thin film composite (TFC) polymeric hollow fiber (HF) membranes are extensively used in industrial gas/vapor separations, water treatment etc. There are numerous advantages to use hollow fibers such as: low energy requirements, simplicity of operation, and high specificity. In the present article we discuss the progress made during the past decade in the preparation of the HF substrate and preparation/modification of the thin selective layer. Their applications in water treatment, dehydration of alcohols via pervaporation and gas/vapor separation are also demonstrated.

Self-consciousness can be considered as the internal disposition to direct attention to oneself. This dispositional tendency can be focused on private aspects of the self, but also on public characteristics of the individual. We examine self-consciousness in online consumer behavior. This concept has been poorly investigated in consumer research. The main objective of this paper is to analyze the influence of the dimensions of self-consciousness in consumer adoption of online shopping. This study is based on a sample of 725 Spanish undergraduates. Results indicated that public self-consciousness is a significant predictor of the adoption of online shopping.

This article presents a self balanced multistage DC-DC step-up converter for photovoltaic applications. Proposed converter topology is designed for unidirectional power transfer and provides a doable solution for photovoltaic applications where voltage is required to be stepped up without magnetic components (Transformer-less and Inductor-less). The output voltage obtained from renewable sources will be low and must be stepped up by using a DC-DC converter for photovoltaic applications. K diodes and K capacitors along with two semiconductor control switch are used in the K-stage proposed converter to obtain an output voltage which is (K+1) times the input voltage. The conspicuous features of proposed topology are i) Magnetic components free (Transformer-less and Inductor-less). ii) Continuous input current iii) Low voltage rating semiconductor devices and capacitors iv) Modularity v) Easy to add a higher number of levels to increase voltage gain vi) Only two control switches with alternating operation and simple control. The proposed converter is compared with recent existing transformer-less and Inductor-less power converter in term of voltage gain, number of devices and cost. The application of proposed circuit is discussed in detail. The proposed converter has been designed with rated power of 60W, input voltage is 24V, output voltage is 100V and switching frequency is 100 kHz. The performance of the converter is verified through experimental and simulation results.

Our first modern global pandemic is caused by a nanosized lipid vesicle, called SARS-CoV-2. Its molecular structure and biogenesis have remarkable similarities with Extracellular Vesicles (EVs, most notably exosomes) that are constantly shed by all cells during their life. Their resemblance may not be a coincidence. Growing body of evidence has shown that EVs have significant roles in various biological processes, including viral infection, transmission and anti-viral response. Drawing comparison with the virus might shed light on how we could fight the COVID-19 disease. This may include novel EV research and diagnostics technologies as well as novel EV-based treatments.

In wireless sensor networks (WSNs), each sensor node can estimate the global parameter from the local data in distributed manner. This paper proposed a robust diffusion estimation algorithm based on minimum error entropy criterion with self-adjusting step-size, which are referred to as diffusion MEE-SAS (DMEE-SAS) algorithm. The DMEE-SAS algorithm has fast speed of convergence and is robust against non-Gaussian noise in the measurements. The detailed performance analysis of the DMEE-SAS algorithm is performed. By combining the DMEE-SAS with diffusion minimum error entropy (DMEE) algorithms, an Improving DMEE-SAS algorithm is proposed, in non-stationary environment where tracking is very important. The Improving DMEE-SAS algorithm can avoid insensitivity of the DMEE-SAS algorithm due to the small effective step-size near the optimal estimator, and obtain a fast convergence speed. Numerical simulations are given to verify the effectiveness and advantages of these proposed algorithms.

Microbial Fuel Cells (MFCs) representing a promising technology for the extract of energy and resources through wastewater and it also offer an economic solution to the problem of environment effluent and energy crisis in near future. The advance device is rather appealing, due its potential benefits, its practical application is, however hindered by several drawbacks, such an internally competing microbial reaction, and low power generation. This report is an endeavor to address various design connected to the MFCs application to wastewater treatment, in particular cost effective bioelectricity from waste water are reviewed and discussed with a multidisciplinary approach. The conclusions drawn herein can be of practical interest to all new researchers dealing with effluent wastewater treatment using MFCs.

The Internet-of-Things (IoT) triggers new types of cyber risks. Therefore, the integration of new IoT devices and services requires a self-assessment of IoT cyber security posture. By security posture this article refers to the cybersecurity strength of an organisation to predict, prevent and respond to cyberthreats. At present, there is a gap in the state-of-the-art, because there are no self-assessment methods for quantifying IoT cyber risk posture. To address this gap, an empirical analysis is performed of 12 cyber risk assessment approaches. The results and the main findings from the analysis is presented as the current and a target risk state for IoT systems, followed by conclusions and recommendations on a transformation roadmap, describing how IoT systems can achieve the target state with a new goal-oriented dependency model. By target state, we refer to the cyber security target that matches the generic security requirements of an organisation. The research paper studies and adapts four alternatives for IoT risk assessment and identifies the goal-oriented dependency modelling as a dominant approach among the risk assessment models studied. The new goal-oriented dependency model in this article enables the assessment of uncontrollable risk states in complex IoT systems and can be used for a quantitative self-assessment of IoT cyber risk posture.

The main objective of this study was to compare the removal efficiency of nutrients using Lactuca sativa, Medicago sativa and Phragmites australis in subsurface flow constructed wetlands with horizontal flow. In order to test water quality, fabricated reactors designed and the plants cultivated in the soil while their root were inside the wastewater. A long time study carried out from spring till end of autumn (9 months) in order to evaluate the difference in removal rate based on the seasonal changes. The highest removal rate was during summer which followed by spring and autumn. Thus, the effect of plants on the removal efficiency of organic matter (COD, BOD), TSS and nutrient (P and TN) appeared to be dependent on the seasonal growth. Phragmites australis the most sensitive species in order the removal of nutrient from wastewater.

Using insights from cybernetics and an information-based understanding of biological systems, a precise, scientifically inspired, definition of free-will is offered and the essential requirements for an agent to possess it in principle are set out. These are: a) there must be a self to self-determine; b) there must be a non-zero probability of more than one option being enacted; c) there must be an internal means of choosing among options (which is not merely random, since randomness is not a choice). For (a) to be fulfilled, the agent of self-determination must be organisationally closed (a `Kantian whole'). For (c) to be fulfilled: d) options must be generated from an internal model of the self which can calculate future states contingent on possible responses; e) choosing among these options requires their evaluation using an internally generated goal defined on an objective function representing the overall `master function' of the agent and f) for `deep free-will', at least two nested levels of choice and goal (d-e) must be enacted by the agent. The agent must also be able to enact its choice in physical reality. The only systems known to meet all these criteria are living organisms, not just humans, but a wide range of organisms. The main impediment to free-will in present-day artificial robots, is their lack of being a Kantian whole. Consciousness does not seem to be a requirement and the minimum complexity for a free-will system may be quite low and include relatively simple life-forms that are at least able to learn.

Silymarin, a mixture of flavonolignan and flavonoid polyphenolic compounds extractable from the milk thistle seed, Silybum marianum, has anti-oxidant, anti-inflammatory, anti-cancer and anti-viral activities potentially useful in the treatment of several liver disorders, such as chronic liver diseases, cirrhosis and hepatocellular carcinoma. Equally promising are the effects of silymarin in protecting the brain from the inflammatory and oxidative stress effects by which metabolic syndrome contributes to neurodegenerative diseases. However, despite clinical trials have proved that silymarin is safe at high doses (>1500 mg/day) in humans, it suffers limiting factors such as low solubility in water (<50 μg/mL), low bioavailability and poor intestinal absorption. To improve its bioavailability and provide a prolonged silymarin release at the site of absorption, the use of nanotechnological strategies appears to be a promising method to potentiate the therapeutic action and promote sustained release of the active herbal extract. The purpose of this study is to review the different nanostructured systems available in literature as delivery strategies to improve the absorption and bioavailability of silymarin.

We discuss the role of water bridging the DNA-enzyme interaction by resorting to recent 1 results showing that London dispersion forces between delocalized electrons of base pairs of DNA 2 are responsible for the formation of dipole modes that can be recognized by Taq polymerase. 3 We describe the dynamical origin of the high efficiency and precise targeting of Taq activity in 4 PCR. The spatiotemporal distribution of interaction couplings, frequencies, amplitudes, and phase 5 modulations comprise a pattern of fields instantiating the electromagnetic image of DNA in its 6 water environment, which is what the polymerase enzyme actually recognizes at long range. The 7 experimental realization of PCR amplification, achieved through replacement of the DNA template 8 by the treatment of pure water with electromagnetic signals recorded from viral and bacterial DNA 9 solutions, is found consistent with the gauge theory paradigm of quantum fields.

Within the field of guilt and shame, two competing perspectives have been advanced. The first, the social-adaptive perspective, proposes that guilt is an inherently adaptive emotion and shame is an inherently maladaptive emotion; thus, those interested in moral character development and psychopathology should work to increase an individual’s guilt-proneness and decrease an individual’s shame-proneness. The functionalist perspective, in contrast, argues that both guilt and shame can serve a person adaptively or maladaptively—depending on the situational appropriateness, duration, intensity, and so forth. This paper reviews the research conducted supporting both positions, critiques some issues with the most widely used guilt- and shame-proneness measure in the social-adaptive research (the TOSCA), and discusses the differences in results found when assessing guilt and shame at the state versus trait level. The conclusion drawn is that although there is broad support for the functionalist perspective across a wide variety of state and trait guilt/shame studies, the functionalist perspective does not yet have the wealth of data supporting it that has been generated by the social-adaptive perspective using the TOSCA. Thus, before a dominant perspective can be identified, researchers need to (1) do more research assessing how the social-adaptive perspective compares to the functionalist perspective at the state level, and (2) do more trait research within the functionalist perspective to compare functionalist guilt- and shame-proneness measures with the TOSCA.

In this work, we investigated the effects of heat treatment on the microstructure, hydrogen storage characteristics and corrosion rate of a Ti₃₄V₄₀Cr₂₄Fe₂ alloy. The arc melted alloy was divided into three samples, two of which were separately quartz-sealed under vacuum and heated to 1000 °C for 1 h; one of these samples was quenched and the other furnace cooled to ambient temperature. The crystal structures of the samples were studied via X-ray diffractometry and scanning electron microscopy. Absorption/desorption characteristics were investigated using a Sievert apparatus. Potentiostat corrosion tests on the alloys were performed using an AutoLab^® corrosion test apparatus and electrochemical cell. All samples exhibited a mixture of body-center-cubic (BCC) and Laves phase structures. The corrosion rate, maximum absorption, and useful capacities increased after both heat treatments. The annealed sample had the highest absorption and reversible capacity. The plateau pressure of the as-cast alloy increased after quenching. The corrosion rate increased from 0.0004 mm/y in as-cast sample to 0.0009 mm/y after annealing and 0.0017 mm/y after quenching, due to a decrease in the Cr-content of the C14 phase.

Current theories of autoimmunity are diverse, sometimes contradictory, and suffer from incompleteness. Although substantial evidence exists that adaptive and innate immunity, sex, genetic predisposition, and the microbiome all play essential roles in autoimmune disease etiologies and pathogenesis, and that antigen processing is altered during disease induction, no existing theory integrates all of these factors through a single, coherent mechanism. In an attempt to focus the field on the need to elucidate such an integrative mechanism, I propose one possibility here that, if nothing else, helps to identify the nature of the problems that need to be addressed. My theory is that autoimmune diseases are induced by normal immunological responses to unique pairs of complementary antigens, at least one of which is a molecular mimic of a host target. Each antigen in the complementary pair induces a complementary immune response (T or B cell); although each immune response is idiotypic in origin, the antigenic complementarity results in what appears to be an idiotype-anti-idiotype relationship between the responses. Additionally, because of the antigenic complementarity, each immune response mimics one of antigens, abrogating the distinction between self and non-self. If at least one of the antigens mimics a host antigen, then the resulting immunological civil war spreads to a host tissue. Complementary antigens also alter antigen processing so that antigens that would normally be proteolytically digested are presented by the major histocompatibility complex (MHC) to T and B cell receptors inducing a cross-reactive immune response. The resulting civil war is supported by the innate immune system due to the complementarity of the initiating antigens.. Complementary antigens stimulate synergistic toll-like receptors (TLR) and/or nucleotide-binding oligomerization receptors (NOD) resulting in up-regulation of cytokine production and further stimulation of the adaptive immune response. Because the immune responses (e.g., antibodies) mimic the initiating antigens, this synergistic activation of innate immunity becomes chronic. Additionally, TLR and NOD function are highly sensitive to sex hormones, some becoming up-regulated and some down-regulated in the presence of either testosterone or estrogens. This sensitivity explains how sex modifies susceptibility to autoimmune diseases. Genetic mutations in TLR, NOD and MHC further alter antigen presentation and the degree to which antigens stimulate an immune response explaining how genetics also modifies susceptibility. Finally, sex hormones also alter the host microbiome, which in turn modulates autoimmune disease risk by shaping the immunological nature of self and by mediating susceptibility to microbial infection. Moreover, it appears that the microbiome camouflages itself from the immune system by mimicking the host antigenic repertoire; the mimicry between the antigens of the microbiome and the host results in selective attacks on microbiome constituents concomitant with any autoimmune attack on host tissues. This antigenic complementarity theory thereby integrates all major elements known to affect, or be affected by, autoimmune diseases and provides a set of testable implications.

The recycling, incineration, and final disposal rate of municipal solid waste (MSW) are calculated based on the total amount of waste input to each facility in many countries. These statistic data have serious limitation in setting the national goal and policy for effective waste management because it is not considering the amount of foreign objectives in the process of each life-cycle stage. This case study is to estimate the actual rates of recycling, incineration, and final disposal by material flow analysis (MFA) after the collection of MSW in Korea. The actual rates of recycling, incineration and final disposal for MSW in 2016 were 49.9%, 32.9% and 23.1% respectively, indicating that the recycling rate was lower by 10.1%, while the incineration and final disposal rates were raised by 7.6% and 8.4% respectively, compared with the statistics for current MSW. In addition, the changed actual rates of recycling, incineration treatment, and final landfill, and variation of waste treatment charge according to treated amounts per treatment method was analyzed. This results of this study will contribute to establish national level of plan on effective waste management.

The proposal that the genetic code was formed on the basis of protein synthesis directed by tRNA dimers is reviewed and updated. The tRNAs paired through the anticodon loops are an indication on the process. Dimers are considered mimics of the ribosomes – structures that hold tRNAs together and facilitate the transferase reaction, and of the translation process – anticodons are at the same time codons for each other. The primitive protein synthesis system gets stabilized when the product peptides are able to bind the producers therewith establishing a self-stimulating production cycle. The chronology of amino acid encoding starts with Glycine and Serine, indicating the metabolic support of the Glycine-Serine C1-assimilation pathway, which is also consistent with evidence on origins of bioenergetics mechanisms. Since it is not possible to reach for substrates simpler than C1 and compounds in the identified pathway are apt for generating the other central metabolic routes, it is considered that protein synthesis is the beginning and center of a succession of sink-effective mechanisms that drive the formation and evolution of the metabolic flow system. Plasticity and diversification of proteins construct the cellular system following the orientation given by the flow and implementing it. Nucleic acid monomers participate in bioenergetics and the polymers are conservative memory systems for the synthesis of proteins. Protoplasmic fission is the final sink-effective mechanism, part of cell reproduction, guaranteeing that proteins don’t accumulate to saturation, which would trigger inhibition.

Background and Objective: China has managed to control the coronavirus disease (COVID-19) with confinement measurements and treatment strategies, while other countries are struggling to contain the spread. This study discusses the guidelines related to COVID-19 in China in order to provide important references for other countries in the fight against COVID-19. Methods: Chinese guidelines relevant to COVID-19 were systematically searched via the China National Knowledge Infrastructure database, YiMaiTong database, and World Health Organization (WHO) COVID-19 database on March 20^th, 2020. Guideline information was extracted, including date of publication, source, objectives and the target population. Guidelines specific to the pharmacological treatment of COVID-19 were further investigated to identify the types of antivirus drugs recommended and to report on how treatment recommendations for COVID-19 have evolved overtime. Results: A total of 114 guidelines were identified, of which 87 were national guidelines and 27 were regional guidelines. The scope of included guidelines consisted of: the diagnosis and treatment of COVID-19, the management of hospital departments and specific diseases during the outbreak of COVID-19. Sixty-four of the included guidelines targeted all COVID-19 patients, while the remaining guidelines concentrated on special patient populations (i.e., geriatric population, pediatric population, and pregnant population) or patients with coexisting diseases. Twenty-three guidelines focused on the pharmacological treatments for all COVID-19 patients. Interferon, Lopinavir/Ritonavir, Ribavirin, Chloroquine, and Umifenovir represented the most recommended antivirus drugs. With the emergence of encouraging results from preclinical and preliminary clinical studies, Chloroquine Phosphate was recommended in the national Diagnosis and Treatment Protocol for Novel Coronavirus Pneumonia (6^th version) on February 19^th, 2020. Thereafter, more detailed guidelines regarding the adjustment of dosage regimens and the monitoring of adverse events of Chloroquine Phosphate were published. To date, 8 Chinese guidelines have recommended Chloroquine Phosphate or Hydroxychloroquine as mainstream antivirus drug for the treatment of COVID-19. Conclusions: China has generated a plethora of guidelines covering almost all aspects of COVID-19. Chloroquine, as one widely affordable treatment, holds great potential to become the gold standard choice as more clinical evidence is shared by researchers from China as well as other countries.

COVID-19 thromboembolic disease has brought all of us back to the drawing board. In COVID-19, pre-existing activated endothelium with increased Von Willebrand factor (VWF), low density lipoprotein (LDL) promoting “self-association” and “sticking” of long VWF strings to the vascular endothelial wall, suppressed ADAMTS13 cleavage of VWF, hypoxia induced upregulation and activation of VWF, fibrous network from neutrophil extracellular traps (NETs) with free DNA and histone, all appear to be initiating the thrombogenesis. Worsening complement activation, cytokine storm and resulting endothelial destruction, unregulated thrombogenesis leads to vascular occlusions and hypoxia. At this stage, the presence of abundant extracellular DNA, histone and -defensins appears worse than the SARS-CoV-2 itself. Previously observed in vitro mechanisms like histone “auto-activating” prothrombin, histone activated platelets generating thrombin without FXII, thrombin and plasmin cleaving complement C5 appears highly likely in COVID-19. Megakaryocytes are actively producing platelets in the lungs and appear to play a major role in thrombogenesis of COVID-19 raising suspicion of emperipolesis. This focused review is a compilation of my observations in relation to the pathophysiology of the intravascular environment, mainly in COVID-19 lungs. Pathophysiology based clinical trials are paramount in reducing morbidity and mortality in COVID-19.

Highly flexible manufacturing systems require continuous run-time (self-) optimization of processes with respect to various parameters, e.g. efficiency, availability, energy consumption etc. A promising approach for achieving (self-) optimization in manufacturing systems is the usage of the context sensitivity approach. Thereby the Cyber-Physical Systems play an important role as sources of information to achieve context sensitivity. In this paper it is demonstrated how context sensitivity can be used to realize a holistic solution for (self-) optimization of discrete flexible manufacturing systems, by making use of Cyber-Physical System integrated in manufacturing systems/processes. A generic approach for context sensitivity, based on self-learning algorithms, is proposed aiming at a various manufacturing systems. The new solution is propos encompassing run-time context extractor and optimizer. Based on the self-learning module both context extraction and optimizer are continuously learning and improving their performance. The solution is following Service Oriented Architecture principles. The generic solution is developed and then applied to two very different manufacturing processes. This paper proposes a holistic solution to achieve context sensitivity for Flexible Manufacturing Systems, whereby the knowledge created by applying the context sensitivity approach can be used for (self-) optimization of manufacturing processes.

We present the AI-discovered aetiology of COVID-19, based on a precise disease model of COVID-19 built under five weeks that best matches the epidemiological characteristics, transmission dynamics, clinical features, and biological properties of COVID-19 and consistently explains the rapidly expanding COVID-19 literature. We present that SARS-CoV-2 implements a unique unbiased survival strategy of balancing viral replication with viral spread by increasing its dependence on (i) ACE2-expressing cells for viral entry and spread, (ii) PI3K signaling in ACE2-expressing cells for viral replication and egress, and (iii) viral-non-structural-and-accessory-protein-dependent immunomodulation to balance viral spread and viral replication. We further propose the combination of irinotecan (an in-market topoisomerase I inhibitor) and etoposide (an in-market topoisomerase IIinhibitor) could potentially be an exceptionally effective treatment to protect critically ill patients from death caused by COVID-19-specific cytokine storms triggered by sepsis, ARDS, and other fatal comorbidities.

This paper investigates the evolution of microstructures and precipitations of an ultra-low iron alloy 625 subjected to long term aging treatment by scanning electron microscope (SEM) and X-ray diffraction(XRD). Use ASTM G28A acid Fe3(SO4)2 erosion to represent intergranular corrosion weightlessness and corrosive morphology. The result shows that alloy at 750C by aging treatment for 40h, precipitated γ'' phase in the grain boundary. In high density area of γ'' phase, occurs γ'' phase to δ phase degeneration transformation by aging treatment for 200h and the needle-like δ phase becomes more with time prolonged. And γ'' phase degenerated to δ phase completely until treated for 1000h. The sample which has aging treatment tends to have intergranular corrosion and mainly because alloy element spreading leads to dilution area and grain boundary precipitated phase, plus interlaced δ phase’s dissolving, which makes sample grain particle fall off and this results in apparent weightlessness. The weightlessness rate(WLR) is related with precipitated volume score. With aging sensitization time change, can be described by Johnson-Mehl-Avrami equation, i.e.: $WLR=44.32\left[1-\text{exp}\left(-\frac{t}{10.99}\right)\right]+44.62\left[1-\text{exp}\left(-\frac{t}{327.8}\right)\right]+1.267\left(mm/a\right)$

Social distancing, washing hands and good hygiene are essential and currently the most potent methods available to curb down the unprecedented speed by which the new coronavirus is spreading across the globe. Even under lockdown, which is necessary to significantly reduce the number of people that get infected by an ill person, are there additional measures that each of us can embrace to even further reduce the risk of infection and the severity of the COVID-19 disease? Given the lack of licensed drugs that target SARS-CoV-2 specifically, we have to look into additional non-specific defense mechanisms that animals and humans evolved to protect themselves from pathogen invasions. The goal of this article is to describe how various of our non-specific defense mechanisms work, which actually precede the inflammatory response, and to discuss whether we can exploit the unique features of the coronavirus envelope and the self-cleaning machinery of the human respiratory tract to strengthen our self-defense. The challenge is to actively interfere with supportive measures during the short time window between getting exposed and before an inflammatory response gets initiated.

In most industrialized countries, screening programs for cervical cancer have shifted from cytology (Pap smear or ThinPrep) alone on clinician-obtained samples to the addition of screening for human papillomavirus (HPV), its main causative agent. For HPV testing, self-sampling instead of clinician-sampling has proven to be equally accurate, in particular for assays that use nucleic acid amplification techniques. In addition, HPV testing of self-collected samples in combination with a follow-up Pap smear in case of a positive result is more effective in detecting precancerous lesions than a Pap smear alone. Self-sampling for HPV testing has already been adopted by some countries, while others have started trials to evaluate its incorporation into national cervical cancer screening programs. Self-sampling may result in more individuals willing to participate in cervical cancer screening, because it removes many of the barriers that prevent women, especially those in low socioeconomic and minority populations, from participating in regular screening programs. Several studies have shown that the majority of women who have been underscreened but who tested HPV-positive in a self-obtained sample, will visit a clinic for follow-up diagnosis and management. Additionally, a self-collected sample can also be used for vaginal microbiome analysis, which can provide additional information about HPV infection persistence as well as vaginal health in general.

The scarcity and pollution of freshwater are extremely crucial issues today and the expansion of water reuse have been considered as an option to reduce its impact. This study aims to assess the efficiency of an integrated greywater treatment system and hydroponic lettuce production as a part of a green wall structure and to evaluate the health risk associated with the production and consumption of lettuce through quantitative microbial risk assessment (QMRA) and chemical health risk assessment. The study was conducted based on the unique configuration of source separation system; on-site greywater treatment system; green wall structure as a polishing step; and hydroponic lettuce production in the green wall structure. The final effluent from the system was used to grow three lettuce varieties by adding urine as a nutrient solution. Both water samples and plant biomass were collected and tested for E. coli and heavy metals contamination. The system has gained a cumulative 5.1 log10 reduction of E. coli in the final effluent and no E. coli found in the plant biomass. QMRA results indicated that the system attained the health-based targets, 10–6 DALYs per person per year. Similarly, health risk index (HRI) and targeted hazard quotient (THQ) results did not exceed the permissible level, thus the chemical health risk concern was insignificant.

Many clinical research datasets have a large percentage of missing values that directly impacts their usefulness in yielding high accuracy classifiers when used for training in supervised machine learning. While missing value imputation methods have been shown to work well with smaller percentages of missing values, their ability to impute sparse clinical research data can be problem specific. We previously attempted to learn quantitative guidelines for ordering cardiac magnetic resonance imaging during the evaluation for pediatric cardiomyopathy, but missing data significantly reduced our usable sample size. In this work, we sought to determine if increasing the usable sample size through imputation would allow us to learn better guidelines. We first review several machine learning methods for estimating missing data. Then, we apply four popular methods (mean imputation, decision tree, k-nearest neighbors, and self-organizing maps) to a clinical research dataset of pediatric patients undergoing evaluation for cardiomyopathy. Using Bayesian Rule Learning (BRL) to learn ruleset models, we compared the performance of imputation-augmented models versus unaugmented models. We found that all four imputation-augmented models performed similarly to unaugmented models. While imputation did not improve performance, it did provide evidence for the robustness of our learned models.

The recent pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread so rapidly and severely affected the people of almost every country in the world. The highly contagious nature of this virus makes it difficult to take control of the present pandemic situation. With no specific treatment available, the coronavirus disease 2019 (COVID-19) presents a threat to people of all ages including the elderly people and people with other medical complications as a vulnerable group to this disease. Better understanding of viral pathogenesis, appropriate preventive measures, early diagnosis and supportive treatments of the infected patients are now the general solutions to fight against this viral transmission. But, as an emerging disease, most about it remains still poorly understood. This article holds an overview on the origin and structure, pathogenesis, diagnosis and possible therapeutic options for the causative agent, SARS-CoV-2 and disease, COVID-19. However, few therapeutic options, laboratory experiments and other strategies proposed here need to be further clinically tested.

Growing crystals of nickel niobate (NiNb2O6), we noticed that changing growth conditions allowed our material to enter different areas of the phase diagram. In particular, we found that excess material accumulated within and above the liquid zone. Analysis showed that this was an unincorporated constituent. Changing the ratio of the constituent oxides - an excess of ~4% of either NiO or Nb2O5 gave us the opportunity to investigate changes in zone stability, melting temperature and quality of the resulting crystal. We found that a small excess of nickel oxide decreases the melting temperature significantly, and created the best pseudo-rutile NiNb2O6 crystal studied, while higher amounts of niobium oxide allowed us to stabilize the NiNb2O6 columbite phase. This research reinforces the idea that self-flux as a travelling solvent can significantly impact crystal growth parameters and quality.

The scratch test consists in pushing a tool across the surface of a material at a given penetration depth or applied load. It has several applications in Science and Engineering including strength testing, damage and quality control of thin films and coatings. Despite numerous attempts in scientific literature, the application of scratch test to characterizations of fracture properties remains a heavily controversial topic. Therefore, this investigation arises as an experimental study in order to assess the fracture toughness using scratch test. A study on the effect of cryogenic treatment, performed after tempering, on fracture toughness, via scratch test experiments, of different tool steels has been made. A laboratory investigation on AISI D2, AISI M2 and X105CrCoMo18 steel confirms the possibility of increasing the fracture toughness by carrying out the cryogenic treatment after the usual heat treatment

Although suicide is a major public health issue worldwide, we understand little of the onset and development of suicidal behavior. Suicidal behavior is argued to be the end result of the complex interaction between psychological, social and biological factors. Epidemiological studies resulted in a range of risk factors for suicidal behavior, but we do not yet understand how their interaction increases the risk for suicidal behavior. A new approach called network analysis can help us better understand this process as it allows to visualize and quantify complex association between many different symptoms or risk factors. A network analysis of data contain information on suicidal patients can help us understand how risk factors interact and how their interaction is related to suicidal thoughts and behaviour. A network perspective has been successfully applied to the field of depression and psychosis, but not yet to the field of suicidology. In this theoretical article, I will introduce the concept of network analysis to the field of suicide prevention, and offer directions for future applications and studies.

Antibody-Drug Conjugates (ADCs) are a powerful therapeutic modality for cancer treatment. ADCs are multi-functional biologics in which a disease-targeting antibody is conjugated to an effector payload molecule through a linker. The success of currently used ADCs has been largely attributed to the development of linker systems which allow targeted release of cytocidal payload drugs inside cancer cells. Many lysosomal proteases are over-expressed in human cancers. They can effectively cleave a variety of peptide sequences, which can be exploited in the design of ADC linker systems. As a well-established linker, valine-citrulline-p-aminobenzyl carbamate (ValCitPABC) is used in many ADCs that are already approved or under preclinical and clinical development. Although ValCitPABC and related linkers are readily cleaved by cathepsins in the lysosome while remaining reasonably stable in human plasma, many studies have shown that they are susceptible to carboxylesterase 1C (Ces1C) in mouse and rat plasma, which hinders preclinical evaluation of the ADCs. Furthermore, neutropenia and thrombocytopenia, two of the most commonly observed dose-limiting adverse effects of ADCs, are believed to result from the premature hydrolysis of ValCitPABC by human neutrophil elastase. In addition to cathepsin-cleavable linkers, there is also growing interest in legumain-sensitive linkers for ADC development. Increasing plasma stability while maintaining lysosomal cleavability of ADC linkers is an objective of intensive current research. This review reports recent advances in the design and structure-activity relationship studies of various peptide/peptidomimetic linkers in this field.

Serious damage caused by floor heave in the coal given chamber of a vertical coal bunker is one of the challenges faced in underground coal mines. Engineering practice shows that it is more difficult to maintain the coal given chamber (CGC) than a roadway. More importantly, repairing the CGC during mining practice will pose major safety risks and reduce production. Based on the case of the serious collapse that occurred in the bearing structure of the CGC at the lower part of the 214# coal bunker in Xiashijie mine, China, this work analysed (i) the main factors influencing floor heave and (ii) the failure mechanism of the load-bearing structure in the CGC using FLAC^2D numerical models and expansion experiment. The analysis results indicate that: the floor heave, caused mainly by mine water, is the basic reason leading to the instability and repeated failure of the CGC in the 214# coal bunker. Then a new coal bunker, without building the CGC, is proposed and put into practice to replace the 214# coal bunker. The FLAC^3D software program is adopted to establish the numerical model of the wall-mounted coal bunker (WMCB), and the stability of the rock surrounding the WMCB is simulated and analysed. The results show that: (1) the rock surrounding the sandstone segment is basically stable. (2) The surrounding rock in the coal seam segment, which moves into the inside of the bunker, is the main zone of deformation for the entire rock mass surrounding the bunker. Then the surrounding rock is controlled effectively by means of high-strength bolt–cable combined supporting technology. According to the geological conditions of the WMCB, the self-bearing system, which includes (i) H-steel beams, (ii) H-steel brackets, and (iii) self-locking anchor cables, is established and serves as a substitute for the CGC to transfer the whole weight of the bunker to stable surrounding rock. The stability of the new coal bunker has been verified by field testing, and the coal mine has gained economic benefit to a value of 158.026174 million RMB over three years. The new WMCB thus made production more effective and can provide helpful references for construction of vertical bunkers under similar geological conditions.

The use of flexible sensors has tripled over the last decade due to the increased demand in various fields including health monitoring, food packaging, electronic skins and soft robotics. Flexible sensors have the ability to be bent and stretched during use and can still maintain their electrical and mechanical properties. This gives them an advantage over rigid sensors that lose their sensitivity when subject to bending. Advancements in 3D printing have enabled the development of tailored flexible sensors. Various additive manufacturing methods are being used to develop these sensors including inkjet printing, aerosol jet printing, fused deposition modelling, direct ink writing, selective laser melting and others. Hydrogels have gained much attention in the literature due to their self-healing and shape transforming. Self-healing enables the sensor to recover from damages such as cracks and cuts incurred during use and this enables the sensor to have a longer operating life and stability. Various polymers are used as substrates on which the sensing conductive material is placed. Polymers including polydimethylsiloxane (PDMS), polyvinyl acetate (PVA), and Kapton are extensively used in flexible sensors. The most widely used nanomaterials in flexible sensors are carbon and silver, however, other nanomaterials such as iron, copper, manganese dioxide and gold are also used to provide controlled levels of conductivity or other functional properties.

Development of early math skills is linked to future success in mathematics and other academics. Educational videogames have been shown to promote academic achievement; however, few rigorous studies have evaluated the use of educational videogames in supporting math development, especially in early primary education. In the current study, an open-label randomized controlled trial was conducted involving 134 first grade students to determine, using standardized assessments, the impact of the educational mathematics tablet-based videogame, Knowledge Battle, on math scores and self-competency. Overall, Knowledge Battle did improve math skills in participants who played the game. Among those with lower pre-game math skills, the Knowledge Battle group’s mean math score increased more than the control group’s mean math score (9.7 vs. 6.0; p=0.02). There was no association between perceived sense of self-competency and total math score (p=0.8141). However, players who had a higher sense of self-competency were more likely to enjoy playing the game. In conclusion, our findings suggest that Knowledge Battle was an acceptable and enjoyable educational mathematical videogame for first grade students, and may be most impactful for those with low math skills.

Structural DNA nanotechnology provides an excellent foundation for diverse nanoscale shapes that can be used in various bioapplications and materials research. From all existing DNA assembly techniques, DNA origami has proven to be the most robust one for creating custom nanoshapes. Since its invention in 2006, building from the bottom up using DNA has drastically advanced, and therefore, more and more complex DNA-based systems have become accessible. So far, vast majority of the demonstrated DNA origami frameworks are static by nature, but interestingly, there also exist dynamic DNA origami devices that are increasingly coming into view. In this review, we discuss DNA origami nanostructures that perform controlled translational or rotational movement triggered by predefined DNA strands, various molecular interactions and/or other external stimuli such as light, pH, temperature and electromagnetic fields. The rapid evolution of such dynamic DNA origami tools will undoubtedly have a significant impact on molecular scale precision measurements, targeted drug delivery and diagnostics, but they can also play a role in development of optical/plasmonic sensors, nanophotonic devices and nanorobotics for numerous different tasks.

Hydrophilic coatings have recently emerged as a new approach to avoid the adhesion of (bio)organisms on surfaces immersed in water. In these coatings the hydrophilic character is crucial for the anti-fouling (AF) performance. However, this property can be rapidly lost due to the inevitable damages which occur at the surface, reducing the long-term effectiveness of the AF functionality. We report hydrophilic polycarbonate-mPEG polyurethane coatings with tunable hydrophilic properties as well as an excellent and long-term stability in water. The coatings exhibit low protein adhesion values and are able to self-replenish their hydrophilicity after damage, due to the existence of a reservoir of hydrophilic dangling chains incorporated in the bulk. The combination of low T_g and sufficient mobility of the mPEG dangling chains (enabled by chains with higher molecular weight) proved to be crucial to ensure autonomous surface hydrophilicity recovery when the coatings were immersed in water. This coatings and design approach offer new possibilities towards high performance AF coatings with an extended service life-time which can be used in several major applications areas, such as marine and biomedical coatings, with major economic and environmental benefits.

Aim of this research paper is to introduce a novel method of hybrid orthodontic tooth-borne distalizer treatment of class II malocclusion by using 3D printed biocompatible personalized distalizer. Explains 3D designing, printing and clinical application of individualized biocompatible medical device dedicated for orthodontic teeth distalization. Compares such distalizer manufactured from two different biocompatible photopolymers (white and transparent). Evaluates their clinical performance and also patients’ aesthetical perception. Clinical part includes comparison of treatment debonding on the set of 12 complete orthodontic treatments with uni-lateral class II malocclusion managed with hybrid approach (CAT-Invisalign with 3D printed distalizer). Paper offers an evaluation of the personalized distalizer functioning in regard to current publications and comparison to conventional prefabricated alternatives like Carriere® Distalizer™ appliance. Results showed no significance of material differences on clinical performance of such individualized distalizers. Research showed preference of patients towards transparent biocompatible photopolymer instead of white A2 shade.

Social media and other web 2.0 tools have provided users the platform to interact and also disclose personal information not only with their friends and acquaintances, but also with relative strangers with unprecedented ease. This has enhanced the ability of people to share more about themselves, their families, and their friends through a variety of media including text, photo, and video, thus developing and sustaining social and business relationships. The purpose of the paper is to identify the factors that predict self-disclosure on social networking sites within the Ghanaian context. Data was collected from 452 students in three leading universities in Ghana and analyzed with Partial Least Square-Structural Equation Modeling. Results from the study revealed that all variables in the proposed model with the exception of interaction and perceived control were significant predictors of self-disclosure with privacy risk being the most significant predictor. In all, the model accounted for 54.6 percent of the variance in self disclosure. The implications and limitations of the current study are discussed and directions for future research proposed.

Partial differential representation of self-similarity feature has been derived from notion of the homogenous function in general sense. This representation allows consideration of stochastic self-similar systems. As well as the partial differential representation allows consideration of Stochastic Partial Differential Equation.

BACKGROUND: From March to April 2020, Spain was the center of the SARS-CoV-2 pandemic, particularly Madrid with approximately 30% of the cases in Spain. The aim of this study is to report the suspected serious adverse drug reactions (SADRs) in COVID-19 patients versus non-COVID-19 patients detected by the prospective pharmacovigilance program based on automatic laboratory signals (ALSs) in the hospital (PPLSH) during that period. We also compared the results with the suspected SADRs detected during the same period for 2019. METHODS: All ALSs that reflected potential SADRs (including neutropenia, pancytopenia, thrombocytopenia, anemia, eosinophilia, leukocytes in cerebrospinal fluid, hepatitis, pancreatitis, acute kidney injury, rhabdomyolysis and hyponatremia were prospectively monitored in hospitalized patients during the study periods. We analyzed the incidence and the distribution of causative drugs for the COVID-19 patients. RESULTS: The incidence rate of SADRs detected in the COVID-19 patients was 760.63 (95% CI 707.89–816.01) per 10,000 patients, 4.75-fold higher than the SADR rate for non-COVID-19 patients (160.15 per 10,000 patients,95% CI 137.09–186.80), and 5.84-fold higher than the SADR rate detected for the same period in 2019 (130.19 per 10,000 patients, 95% CI 109.53–154.36). The most frequently related drugs were tocilizumab (59.84%), dexketoprofen (13.93%), azithromycin (8.43%), lopinavir-ritonavir (7.35%), dexamethasone (7.62%), and chloroquine/hydroxychloroquine (6.91%). CONCLUSIONS: The incidence rate of SADRs detected by the PPSLH in patients with COVID-19 was 4.75-fold higher than that of the non-COVID-19 patients. Caution is recommended when using medications for COVID-19 patients, especially drugs that are hepatotoxic, myotoxic, and those that induce thromboembolic events.

Microalgae are known as a rich source of bioactive compounds which exhibit different biological activities. Increased demand for sustainable biomass for production of important bioactive components with various potential especially therapeutic applications has resulted in noticeable interest in algae. Utilization of microalgae in multiple scopes has been growing in various industries ranging from harnessing renewable energy to exploitation of high-value products. The focuses of this review are on the isolation of bioactive compounds from microalgae regarding different metabolites which are currently used and new possible applications of the compounds in industries and future prospects. Moreover, this work discusses the advantage, potential new beneficial strains, applications, limitations, research gaps and future prospect of microalgae in industry.

Inorganic nanoparticles based on magnetite improve the mechanical, thermal, and magnetic properties of microporous cryogel polymer composites. Here we report the synthesis of microporous cryogel based on the crosslinked sodium vinyl sulfonate (Na-VS) and 2-acrylamido-2-methylpropane sulfonic acid sodium salt (Na-AMPS). The magnetite nanoparticles were inserted into Na-VS/Na-AMPS cryogel either during its crosslinking polymerization or by in-situ technique after its crosslinking. The morphology, particle sizes, thermal stability and magnetite contents of Na-VS/Na-AMPS cryogel and its magnetite composites were investigated. The prepared Na-VS/Na-AMPS cryogel and its magnetite composites were used as adsorbents for methylene blue (MB) cationic dye using optimum conditions. The magnetite Na-VS/Na-AMPS cryogel composite prepared by in-situ technique achieved the best adsorption MB removal capacity for 7 cycles among the other adsorbents via chemical adsorption mechanism at room temperature.

In previous studies we found that generalized functions can be smooth, discrete, periodic or discrete periodic and they can either be local or global and they are regular or generalized functions. We also saw that these properties were related to Poisson’s summation formula on one hand and to Heisenberg’s uncertainty principle on the other. In this paper, we interlink these studies and show that scalars (real or complex numbers) considered as trivial functions are discrete and periodic, local and global as well as regular and generalized, simultaneously. However, this is also a paradox because it means that Dirac’s δ and 1 (its Fourier transform) coincide. They both are unity. We show that δ and 1 coincide in the sense of scalars (real or complex numbers) but they differ in the sense of (generalized) functions. This result can moreover be related to Max Born’s principle of reciprocity. It also answers an open question in present-day quantum mechanics because it means that the Dirac delta squared is simply delta.

Almond is worldwide consumed and renowned as a valuable healthy food. In spite of this, it is also a potent source of allergenic proteins able to trigger several mild to life-threatening immunoreactions. Food processing proved to alter biochemical characteristics of proteins, thus affecting the respective allergenicity. In this paper we investigated the effect of autoclaving, preceded or not by a hydration step, on the biochemical and immunological properties of almond proteins. Any variation in the stability and immunoreactivity of almond proteins extracted from the treated materials, were evaluated by total protein quantification, ELISA assay and protein profiling by electrophoresis-based separation (SDS-PAGE). The autoclaving alone was found to weakly affect almond proteins stability, despite what observed for the combination of hydration and autoclaving, which resulted in a loss of approximately 70% of total protein content compared to untreated sample, and in a final negligible immunoreactivity, as well. The final SDS-PAGE protein pattern recorded for almonds hydrated and autoclaved disclosed significant changes. In addition, the same samples were further submitted to in vitro simulated gastro-duodenal (GI) digestion to evaluate potential changes induced by these processing on allergens digestibility. Digestion products were identified by HPLC-HRMS/MS analysis followed by software-based data mining, and complementary information were provided by analyzing the proteolytic fragments lower that 6 kDa in size. The autoclave based treatment was found not to alter the allergens digestibility, whereas an increased susceptibility to proteolytic action of digestive enzymes was observed in almonds subjected to the combination of prehydration and autoclaving. Finally, the residual immunoreactivity of the GI resistant peptides was investigated in-silico by bioinformatic tools, confirming that by following both approaches, no epitopes survived the almond digestion, thus demonstrating the potential effectiveness of these treatments to reduce almond allergenicity.

Pervasive and wide-ranging cognitive deficits are a core feature of schizophrenia and an important determinant of long-term functional outcome. The lack of sufficiently effective treatments for cognitive impairment associated with schizophrenia (CIAS) represents a major unmet need and a central roadblock towards recovery. This is partly due to the current therapeutic focus on clinical symptoms, and the relative neglect of cognitive impairments despite their functionally disabling effects. Furthermore, effective treatment is impeded by our limited knowledge of the complex pathophysiology, which gives rise to perturbed information processing. Here, we review mechanisms and effectiveness of available pharmacological and non-pharmacological treatments for CIAS. Current evidence indicates, that while techniques which broadly enhance neural plasticity show the greatest therapeutic potential, effect sizes are at best moderate. Among other reasons, this is due to a considerable heterogeneity of responses to individual interventions. Furthermore, we discuss how recent conceptual advances in operationalizing cognitive impairments based on cognitive neuroscience have the potential to address these issues and facilitate the development of novel treatment strategies for CIAS. This includes more clearly elucidating pathophysiological mechanisms in both humans and animal models, identifying new treatment targets as well as establishing biomarkers for a better prediction of treatment responses.

This study aimed to know the conditioning factors of the transition process to the self-care of women diagnosed with HIV/AIDS. This qualitative study was carried out from June to September 2015 with seven seropositive women, users of a specialized service in sexually transmitted diseases in the municipality of Imperatriz, Maranhão State, Brazil. For the data collection, an individual interview was used, and data analysis was performed by content analysis delineated by Hsieh and Shannon (2005). The resources that influence the self-care in the transition process of women with HIV/AIDS are represented by personal conditioning factors, such as the meaning they attribute to the living with the disease, personal attitudes and cultural beliefs, socioeconomic status, preparation and knowledge about the disease, and by conditioning factors found in the community and society. The transition theory can provide important insights about the resources present in the adaptation process of women diagnosed with HIV so that they can perform their self-care satisfactorily.

Owing to their unique physicochemical properties, nanoparticles are used in a variety of ways in the field of cancer treatment, including imaging, drug delivery, and photothermal and photodynamic therapies. The fascinating properties of nanoparticles are determined by their size, morphology, and constituent elements, and various synthetic methods and post-synthetic techniques have been applied to control these factors. Herein, we present examples of shape and composition control through galvanic replacement, a technique that exploits redox potential differences between elements to induce spontaneous ion-exchange and highlight its specific contributions to cancer treatment applications. The present article identifies the recent advances in nanoparticle formation techniques and discusses the future outlook of the field.

Water treatment efficiency of several filter media such as perlite, modified (silicated) perlite, zeolite and sand were studied on wastewater. This study contains 2 distinct experiments which the first one emphasize on the modified perlite’s performance in removing turbidity which has been gone through 3 phases including low turbidity model water, mid turbidity and high turbidity model water; the second experiment underlines the differentiation between 3 evolutionary material based on perlite which undergoes the filtration process with certain turbid model water. It was dedicated that modified perlite removed more than 90% of turbidity and it functions better than other materials with high turbidity (more than100 NTU). The experiments have been conducted with sodium silicate perlite, normal perlite and synthetic zeolite perlite in order to determine the optimized material which is able to be substituted with perlite in the filtration process.

Using the culture-work-health model, this study investigates the factors influencing the quality of life of maritime workers. This study conducted a survey of 320 maritime workers who have experience living and working on a ship for more than six months. This self-administered questionnaire included questions on organizational culture and support, self-efficacy, perceived fatigue, as well as the quality of work life. Organizational culture and self-efficacy were identified as factors affecting the quality of work life, while organizational support was found to have an indirect effect after passing through self-efficacy and perceived fatigue. The final model accounts for 63.1% of the variance in maritime workers’ quality of life. As such, this study shows that self-efficacy is important for the quality of life of maritime workers, having both direct and indirect effects. Moreover, organizational support may prove the primary intervention point for relieving perceived fatigue and enhancing self-efficacy, thus improving the quality of work life.

The improvement of mechanical properties of cantala fiber and its composites. Treatments including alkali, silane, and the combination of both were carried out to modify the fiber surface. The influence of chemical treatments on fiber properties such as the degree of crystallinity and tensile strength was investigated. A variety of short cantala fiber reinforced rHDPE composites were produced by hot press, and the effect of fiber treatment on the flexural strength of composites was observed. SEM observations also carried out to highlight these changes. The result shows that alkali treatment improves tensile strength and tensile modulus of alkali treated fiber (NF12) which was predicted as a result of the enhancement of the cellulose crystallinity. In contrast, the tensile strength and tensile modulus of silane (SF05) and alkali-silane treated fiber (NSF05) decreased compared to untreated fiber (UF) which is caused by the addition of amorphous material. The tensile strength of alkali-silane treated fiber (NSF05) was lower than alkali treated fiber (NF12), but the composites prepared with NSF05 showed the highest increment of flexural strength of 25.9%. This may be due the combination of alkali and silane treatment helped in the better formation of fiber-matrix interface adhesion.

Self-healing is the capability of materials to repair themselves after damage has occurred, usually by interaction between molecules or chains. Physical and chemical processes are applied for the preparation of self-healing systems. There are different approaches for these systems such as heterogeneous systems, shape memory effects, hydrogen bonding or covalent-bond interaction, diffusion and flow dynamics. Self-healing mechanisms can occur in particular by heat and light exposure or by reconnection without direct effect. The applications of these systems display an increasing trend in both R&D and industry sectors. Moreover, self-healing systems and their energy storage applications are currently getting great importance. This review aims to provide general information on recent developments in self-healing materials and their energy applications in view of the critical importance of self-healing systems for lithium-ion batteries (LIBs). In the first part of the review, an introduction about self-healing mechanisms and design strategies of self-healing materials is given. Then, selected important healing materials in the literature for the anodes of LIBs are mentioned in the second part. The results and future perspectives are stated in the conclusion section.

Viruses have established symbiotic relationships with almost every other living organism on Earth and at all levels of biological organisation, from other viruses up to entire ecosystems. In most cases, peacefully coexisting with their hosts, but in most relevant cases, parasitising them and inducing diseases. Viruses are playing an essential role in shaping the eco-evolutionary dynamics of their hosts, and have been also involved in some of the major evolutionary innovations either by working as vectors of genetic information or by being themselves coopted by the host into their genomes. Viruses can be studied at different levels of biological organisation, from the molecular mechanisms of genome replication, gene expression and encapsidation, to global pandemics. All these levels are different and yet connected through the presence of threshold conditions allowing for the formation of a capsid, the loss of genetic information or epidemic spreading. These thresholds, as it occurs with temperatures separating phases in a liquid, define sharp qualitative types of behaviour. These {\em phase transitions} are very well known in Physics. They have been studied by means of simple, but powerful models able to capture their essential properties, allowing to understand them. Can the physics of phase transitions be an inspiration for our understanding of viral dynamics at different scales? Here we review well-known examples of transition phenomena in virology and their simplest mathematical modelling approaches. We suggest that the advantages of abstract, simplified pictures used in Physics are also the key to properly understand the origins and evolution of complexity in viruses. By means of several examples, we explore this multilevel landscape and how minimal models provide deep insights into a diverse array of problems. The relevance of these transitions in connecting dynamical patterns across levels and their evolutionary and clinical implications are outlined.

The Photovoltaic modules are usually installed on the ground which exposes it to surface deposition of foreign particles. In the Middle East and North Africa region, the primary culprit is dust and sand. They form an insulating and opaque layer on the surface of the glass, which obstructs its heat transfer and optical properties, thereby reducing the overall yield efficiency of the solar panel. Cleaning of this layer is critical to the operation of the solar panel and often requires great effort and energy on a large-scale solar array. In this paper, we propose a novel self-cleaning mechanism for solar panels, with an understanding of the structural integrity of the Photovoltaic laminate and application of external mechanical vibration. By applying an external source of vibration, the solar panels vibrate, excites its fundamental frequencies and cleans by its own. The method is analyzed using finite element analysis method and tested using experiments. Our simulation results based on IEC 61215 show that the maximum principal stress and deformation in the critical layers is within limits. Our experimental results prove the proposed theory is feasible and can be extended to large scale solar arrays. Our proposed method is retrofittable and could save money, energy and effort in cleaning the solar arrays, which can replace current techniques.

Currently, SARS-CoV-2 infection which is the causative agent for COVID-19 disease is a worldwide pandemic with more than 100 million global cases and more than 2.0 million deaths (as of January, 2021). While several vaccines for prevention of COVID-19 have already been registered by the regulatory authorities, the problem is that the substitution rate of this virus is estimated to be one change per 2 weeks, thus mutations could arise that threaten the efficacy of vaccines. Unfortunately, there is no current evidence from random clinical trials to recommend any specific post-exposure treatment for patients with suspected or confirmed COVID-19 disease. Here we propose an innovative superinfection therapeutic (SIT) strategy, which could complement the development of prophylactic vaccines. SIT is based on clinical observations that unrelated harmless viruses might interact in patients infected with pathogenic virus. During SIT, the patient benefits from superinfection with an apathogenic double-stranded RNA (dsRNA) virus such as the infectious bursal disease virus (IBDV), which is a powerful activator of the interferon-dependent antiviral gene program. An attenuated vaccine strain of IBDV was already successfully administered to resolve acute and persistent infections induced by two completely different viruses, the hepatitis B (DNA) and C (RNA) viruses (HBV/HCV). The safety of orally administered acid-resistant IBDV strain R903/78 reverse engineered viral drug candidate was demonstrated in 10 stage IV cancer patients who exhausted all conventional therapy. Following repeated oral administration of the virus up to 10⁹ infectious units (IU)/ dose, only mild flu-like side effects were reported in some patients. Proof-of-principle efficacy was demonstrated in an early COVID-19 patient who was successfully treated with 3x10⁶ IU of an attenuated IBDV vaccine. A small scale dose-finding Phase I safety study is proposed.

Ovarian Cancer (OC) is a type of cancer that affects ovaries in women, and is difficult to detect at initial stage due to which it remains as one of the leading causes of cancer death. The ovarian cancer data generated from the Internet of Medical Things (IoMT) was used and a novel approach was proposed for distinguishing the ovarian cancer by utilizing Self Organizing Maps (SOM) and Optimal Recurrent Neural Networks (ORNN). SOM algorithm was utilized for better feature subset selection and was also utilized for separating profitable, understood and intriguing data from huge measures of medical data. In supervised learning techniques, the SOM-based feature selection seems to be a tougher challenge because of the absence of class labels that would guide the search for relevant information to the classifier model. The classification approach can identify ovarian cancer data as benign/malignant. The ovarian cancer detection process can be improved by optimizing the weights of RNN structure using Adaptive Harmony Search Optimization (AHSO). The proposed model in this study can be used to detect cancer at early stages with high accuracy and low Root Mean Square Error (RMSE).

The capacity and the mechanism of the adsorption of aqueous barium (Ba), cobalt (Co), strontium (Sr) and zinc (Zn) by Ecuadorian (NatAllo) and synthetic (SynAllo-1 and SynAllo-2) allophanes were studied as a function of contact time, pH and metal ion concentration using kinetic and equilibrium experiments. The mineralogy, nano-structure and chemical composition of the allophanes were characterized by X-ray diffraction, Fourier transform infrared spectroscopy, transmission electron microscopy and specific surface area analyses. The evolution of adsorption fitted to a pseudo-first-order reaction kinetics, where equilibrium between aqueous metal ions and allophane was reached within < 10 min. The metal ion removal efficiencies varied from 0.7 to 99.7 % at pH 4.0 to 8.5. At equilibrium, the adsorption behavior is better described by the Langmuir model than by the Dubinin-Radushkevich model, yielding sorption capacities of 10.6, 17.2 and 38.6 mg/g for Ba^(2+), 12.4, 19.3 and 29.0 mg/g for HCoO_2^-, 7.2, 15.9 and 34.4 mg/g for Sr^(2+) and 20.9, 26.9 and 36.9 mg/g for Zn^(2+), respectively, by NatAllo, SynAllo-2 and SynAllo-1. The uptake mechanism is based on a physical adsorption process. Allophane holds great potential to remove aqueous metal ions and could be used instead of zeolites, montmorillonite, carbonates and phosphates for wastewater treatment.

Solar cell layers technology has achieved global standing in the solar cell layers deposition process, and it covers the innovative methods and techniques in significant applications. Recent solar cell layers technology has an advanced interest in a refined approach to enhance performance and highlights the importance of recent proficient procedures for manufacturing. For example, the application is used to search for novel materials for solar cells' layers to clarify the current energy crisis. The technological process and various types of solar cells depend on climate change. Among them, layers of solar cells and silicon wafer solar cells are very encouraging. Solar cell layers technology has led to solar cells being a more reasonable active option in design and production. The productivities facilitated by new solar cells still need to be enhanced for the various processes involved in the additional enhancement from Copper Indium Gallium Selenide (CIGS) microfilms to solar cell crystal structure dye-sensitized solar cells. The hydrophobic coating works as an anti-dust coating, enhancing efficiency and decreasing the cost of cleaning solar cells. In Saudi Arabia Majmaah City, most solar projects are in dry regions, where the dusty weather reduces solar cell efficiency. Therefore, combining these two properties and applying an anti-reflective and superhydrophobic coating will increase solar cell efficiency by 20%. Solar cells' crystal structure results are substituted with layers or new materials to balance environmental impact and toxic nature.

We wanted to investigate the current knowledge on the impact of diet on anti-TNF response in inflammatory bowel diseases (IBD), to identify dietary factors that warrant further investigations in relation to anti-TNF treatment response, and, finally, to discuss potential strategies for such investigations. PubMed was searched using specified search terms. One small prospective study on diet and anti-TNF treatment in 56 patients with CD found similar remission rates after 56 weeks among 32 patients with good compliance that received concomitant enteral nutrition and 24 with poor compliance that had no dietary restrictions (78% versus 67%, p = 0.51). A meta-analysis of 295 patients found higher odds of achieving clinical remission and remaining in clinical remission among patients on combination therapy with specialised enteral nutrition and Infliximab (IFX) compared with IFX monotherapy (OR 2.73; 95% CI: 1.73–4.31, p < 0.01, OR 2.93; 95% CI: 1.66–5.17, p < 0.01, respectively). In conclusion, evidence-based knowledge on impact of diet on anti-TNF treatment response for clinical use is scarce. Here we propose a mechanism by which Western style diet high in meat and low in fibre may promote colonic inflammation and potentially impact treatment response to anti-TNF drugs. Further studies using hypothesis-driven and data-driven strategies in observational, animal and interventional studies are warranted.