EVALUATING WATER QUALITY INDEX OF AL HAMMAR MARSH, SOUTH OF IRAQ WITH THE APPLICATION OF GIS TECHNIQUE

This study concerns the water quality index of the Al Hammar marsh. The water quality of station M1, also termed Al-Hamedy, located in the middle of the marsh and related to the Al-Basra governorate, was evaluated from 2011 to 2015, using 12 selected parameters. The parameters include pH, Phosphate (PO4), Nitrate (NO3), Magnesium (Mg), Calcium (Ca), Total hardness (TH), Sodium (Na), Sulphate (SO4), Chloride (Cl), Total dissolved solids (TDS), Alkalinity (Alk.) and Electrical conductivity (EC). The Arithmetic Weighted Index was employed to ascertain the water quality index (WQI) in the Al-Hammar marsh. The findings from this research have been linked to the ArcGIS 10.4.1 software, to produce layers that represent the nature of the spatial distribution of the WQIs, as coloured maps. The results revealed that the marsh quality fell below the class of poor water quality, and the marsh water was brackish due to the high concentration of totally dissolved solids flowing in from the estuaries of the feeding channels coming from the river Euphrates, as well as from the tidal phenomenon via river Shatt Al-Arab

The pipeline for drugs for control and elimination of neglected tropical diseases : 2. Oral anti-infective drugs and drug combinations for off-label use

In its ‘Road map for neglected tropical diseases 2021–2030’, the World Health Organization outlined its targets for control and elimination of neglected tropical diseases (NTDs) and research needed to achieve them. For many NTDs, this includes research for new treatment options for case management and/or preventive chemotherapy. Our review of small-molecule anti-infective drugs recently approved by a stringent regulatory authority (SRA) or in at least Phase 2 clinical development for regulatory approval showed that this pipeline cannot deliver all new treatments needed. WHO guidelines and country policies show that drugs may be recommended for control and elimination for NTDs for which they are not SRA approved (i.e. for ‘off-label’ use) if efficacy and safety data for the relevant NTD are considered sufficient by WHO and country authorities. Here, we are providing an overview of clinical research in the past 10 years evaluating the anti-infective efficacy of oral small-molecule drugs for NTD(s) for which they are neither SRA approved, nor included in current WHO strategies nor, considering the research sponsors, likely to be registered with a SRA for that NTD, if found to be effective and safe. No such research has been done for yaws, guinea worm, Trypanosoma brucei gambiense human African trypanosomiasis (HAT), rabies, trachoma, visceral leishmaniasis, mycetoma, T. b. rhodesiense HAT, echinococcosis, taeniasis/cysticercosis or scabies. Oral drugs evaluated include sparfloxacin and acedapsone for leprosy; rifampicin, rifapentin and moxifloxacin for onchocerciasis; imatinib and levamisole for loiasis; itraconazole, fluconazole, ketoconazole, posaconazole, ravuconazole and disulfiram for Chagas disease, doxycycline and rifampicin for lymphatic filariasis; arterolane, piperaquine, artesunate, artemether, lumefantrine and mefloquine for schistosomiasis; ivermectin, tribendimidine, pyrantel, oxantel and nitazoxanide for soil-transmitted helminths including strongyloidiasis; chloroquine, ivermectin, balapiravir, ribavirin, celgosivir, UV-4B, ivermectin and doxycycline for dengue; streptomycin, amoxicillin, clavulanate for Buruli ulcer; fluconazole and isavuconazonium for mycoses; clarithromycin and dapsone for cutaneous leishmaniasis; and tribendimidine, albendazole, mebendazole and nitazoxanide for foodborne trematodiasis. Additional paths to identification of new treatment options are needed. One promising path is exploitation of the worldwide experience with ‘off-label’ treatment of diseases with insufficient treatment options as pursued by the ‘CURE ID’ initiative. Graphical abstract: [Figure not available: see fulltext.]

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

Background: Many patients with COVID-19 have been treated with plasma containing anti-SARS-CoV-2 antibodies. We aimed to evaluate the safety and efficacy of convalescent plasma therapy in patients admitted to hospital with COVID-19. Methods: This randomised, controlled, open-label, platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]) is assessing several possible treatments in patients hospitalised with COVID-19 in the UK. The trial is underway at 177 NHS hospitals from across the UK. Eligible and consenting patients were randomly assigned (1:1) to receive either usual care alone (usual care group) or usual care plus high-titre convalescent plasma (convalescent plasma group). The primary outcome was 28-day mortality, analysed on an intention-to-treat basis. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936. Findings: Between May 28, 2020, and Jan 15, 2021, 11558 (71%) of 16287 patients enrolled in RECOVERY were eligible to receive convalescent plasma and were assigned to either the convalescent plasma group or the usual care group. There was no significant difference in 28-day mortality between the two groups: 1399 (24%) of 5795 patients in the convalescent plasma group and 1408 (24%) of 5763 patients in the usual care group died within 28 days (rate ratio 1·00, 95% CI 0·93–1·07; p=0·95). The 28-day mortality rate ratio was similar in all prespecified subgroups of patients, including in those patients without detectable SARS-CoV-2 antibodies at randomisation. Allocation to convalescent plasma had no significant effect on the proportion of patients discharged from hospital within 28 days (3832 [66%] patients in the convalescent plasma group vs 3822 [66%] patients in the usual care group; rate ratio 0·99, 95% CI 0·94–1·03; p=0·57). Among those not on invasive mechanical ventilation at randomisation, there was no significant difference in the proportion of patients meeting the composite endpoint of progression to invasive mechanical ventilation or death (1568 [29%] of 5493 patients in the convalescent plasma group vs 1568 [29%] of 5448 patients in the usual care group; rate ratio 0·99, 95% CI 0·93–1·05; p=0·79). Interpretation: In patients hospitalised with COVID-19, high-titre convalescent plasma did not improve survival or other prespecified clinical outcomes. Funding: UK Research and Innovation (Medical Research Council) and National Institute of Health Research

Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Background: In this study, we aimed to evaluate the effects of tocilizumab in adult patients admitted to hospital with COVID-19 with both hypoxia and systemic inflammation. Methods: This randomised, controlled, open-label, platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing several possible treatments in patients hospitalised with COVID-19 in the UK. Those trial participants with hypoxia (oxygen saturation <92% on air or requiring oxygen therapy) and evidence of systemic inflammation (C-reactive protein ≥75 mg/L) were eligible for random assignment in a 1:1 ratio to usual standard of care alone versus usual standard of care plus tocilizumab at a dose of 400 mg–800 mg (depending on weight) given intravenously. A second dose could be given 12–24 h later if the patient's condition had not improved. The primary outcome was 28-day mortality, assessed in the intention-to-treat population. The trial is registered with ISRCTN (50189673) and ClinicalTrials.gov (NCT04381936). Findings: Between April 23, 2020, and Jan 24, 2021, 4116 adults of 21 550 patients enrolled into the RECOVERY trial were included in the assessment of tocilizumab, including 3385 (82%) patients receiving systemic corticosteroids. Overall, 621 (31%) of the 2022 patients allocated tocilizumab and 729 (35%) of the 2094 patients allocated to usual care died within 28 days (rate ratio 0·85; 95% CI 0·76–0·94; p=0·0028). Consistent results were seen in all prespecified subgroups of patients, including those receiving systemic corticosteroids. Patients allocated to tocilizumab were more likely to be discharged from hospital within 28 days (57% vs 50%; rate ratio 1·22; 1·12–1·33; p<0·0001). Among those not receiving invasive mechanical ventilation at baseline, patients allocated tocilizumab were less likely to reach the composite endpoint of invasive mechanical ventilation or death (35% vs 42%; risk ratio 0·84; 95% CI 0·77–0·92; p<0·0001). Interpretation: In hospitalised COVID-19 patients with hypoxia and systemic inflammation, tocilizumab improved survival and other clinical outcomes. These benefits were seen regardless of the amount of respiratory support and were additional to the benefits of systemic corticosteroids. Funding: UK Research and Innovation (Medical Research Council) and National Institute of Health Research

Reducing integrated circuit test cost through improvements in multisite testing and built-in self-test

The semiconductor industry is continually growing, and integrated electronics are increasingly assimilating into our daily lives. As these electronics grow in complexity, the cost of testing them has become a significant challenge to the industry. Two methods that are utilized by test engineers to reduce test costs are parallelism and built-in self-test (BIST). Parallelism is implemented with multisite testing but suffers from site-to-site variations. BIST reduces the tester’s string requirements but faces challenges due to area limitations. In this thesis, two methods to identify site-to-site variations in multisite testing are developed, and an improved switch sizing for BIST solutions is presented. The two algorithms developed identify site-to-site variations in multisite testing by comparing each site’s distribution against an approximation of the parameter’s variation-free distribution. These algorithms produce scores that quantify how much site-to-site variation is present in each site’s data, a capability that traditional inferential statistical tests fail to provide. The two methods were compiled into a software package that was transferred to Texas Instruments. Further efforts were made to utilize the algorithm scores to identify root causes of site-to-site variations. The tester board was simulated using two different simulations methods, and various parameters were extracted. These parameters were correlated with scores from the two methods and the original volume probe data. Preliminary results were obtained that can serve as an initial step to developing a method that automatically identifies issues with test boards that cause site-to-site variations. Finally, an improved area allocation technique is presented that improves shift constancy for analog-to-digital converter BIST. The proposed sizing algorithm was developed after reviewing a previous analog-to-digital converter BIST design. By employing this sizing strategy, the shift constancy of the BIST is improved by a factor of two. Decreasing the voltage shift error allows the USER-SMILE algorithm (the testing method used by the BIST solution) to test higher resolution ADCs

Meerkat Clan Algorithm: A New Swarm Intelligence Algorithm

Evolutionary computation and swarm intelligence meta-heuristics are exceptional instances that environment has been a never-ending source of creativeness. The behavior of bees, bacteria, glow-worms, fireflies and other beings have stirred swarm intelligence scholars to create innovative optimization algorithms. This paper proposes the Meerkat Clan Algorithm (MCA) that is a novel swarm intelligence algorithm resulting from watchful observation of the Meerkat (Suricata suricatta) in the Kalahari Desert in southern Africa. This animal shows an exceptional intelligence, tactical organizational skills, and remarkable directional cleverness in its traversal of the desert when searching for food. A Meerkat Clan Algorithm (MCA) proposed to solve the optimization problems through reach the optimal solution by efficient way comparing with another swarm intelligence. Traveling Salesman Problem uses as a case study to measure the capacity of the proposed algorithm through comparing its results with another swarm intelligence. MCA shows its capacity to solve the Traveling Salesman’s Problem. Its dived the solutions group to sub-group depend of meerkat behavior that gives a good diversity to reach an optimal solution. Paralleled with the current algorithms for resolving TSP by swarm intelligence, it has been displayed that the size of the resolved problems could be enlarged by adopting the algorithm proposed here

Optimisation of multi effect distillation based desalination system for minimum production cost for freshwater via repetitive simulation

The shortage of fresh water resources is a global problem which requires a prompt solution. Thus, the multi effect distillation (MED) was successfully used for the production of fresh water from seawater. Despite the use of MED desalination system extensively, the influence of the number of effects on the fresh water production cost has not been covered in the open literature. Thus, this paper tries to rectify this specific challenge via simulation at given operating conditions of seawater salinity and temperature. The study is performed using a detailed mathematical model contains the suitable cost correlations. gPROMS model builder suite has been used to carry out an extensive simulation. The results of the study show that the lowest fresh water production cost can be achieved at an optimal number of effects of 17 for a certain operating conditions