Severe health conditions can result from lack of knowledge on the bioactive constituents of medicinal plants, as it the main stay of treatment and prevention of diseases in our locality. Hence, the need to examine the therapeutic active ingredients responsible for plants medicinal ability for better health management. This study analyses the phytochemical constitutes and anti – oxidant activity of the bark of lawsonia inermis. Lawsonia inermis bark was collected, cut into pieces and dried at room temperature. The dried sample was pulverized into fine particle. 200g of the pulverized sample was weighed into a 750mL container and was added 300mL absolute ethanol, then allowed to stand for extraction. The solute obtained by evaporating the ethanol was screened for the presence of phyto – components and the result shows alkaloids, glycosides, saponins, phenols, flavonoids, proteins and amino acid as bioactive substances. Also, lawsonia inermis bark displayed an efficient free radical scavenging potential as the anti – oxidant ability showed the percentage KMnO4 radical scavenging activities of 41.4% which shows close competence with the standard ascorbic acid; 47.9% at EC50; This indicate lawsonia inermis bark to exhibit a good potential as antioxidant and could scavenge free radical from the body. The presence of the bioactive substances signifies its usefulness in therapeutic health as agent that could inhibit diseases causing several ailments and as well be a good source for health management control.
{"title":"Phytochemical screening and antioxidant activities of the bark of Lawsonia inermis (Henna) grown in Dekina, Kogi, Nigeria","authors":"Abuh Omachoko Leonard, Isah Aminu Agih, Azeez Ayinla Akeem, Kwasi Ndanusa Benjamin","doi":"10.56919/usci.1122.035","DOIUrl":"https://doi.org/10.56919/usci.1122.035","url":null,"abstract":"\u0000\u0000Severe health conditions can result from lack of knowledge on the bioactive constituents of medicinal plants, as it the main stay of treatment and prevention of diseases in our locality. Hence, the need to examine the therapeutic active ingredients responsible for plants medicinal ability for better health management. This study analyses the phytochemical constitutes and anti – oxidant activity of the bark of lawsonia inermis. Lawsonia inermis bark was collected, cut into pieces and dried at room temperature. The dried sample was pulverized into fine particle. 200g of the pulverized sample was weighed into a 750mL container and was added 300mL absolute ethanol, then allowed to stand for extraction. The solute obtained by evaporating the ethanol was screened for the presence of phyto – components and the result shows alkaloids, glycosides, saponins, phenols, flavonoids, proteins and amino acid as bioactive substances. Also, lawsonia inermis bark displayed an efficient free radical scavenging potential as the anti – oxidant ability showed the percentage KMnO4 radical scavenging activities of 41.4% which shows close competence with the standard ascorbic acid; 47.9% at EC50; This indicate lawsonia inermis bark to exhibit a good potential as antioxidant and could scavenge free radical from the body. The presence of the bioactive substances signifies its usefulness in therapeutic health as agent that could inhibit diseases causing several ailments and as well be a good source for health management control. \u0000\u0000","PeriodicalId":235595,"journal":{"name":"UMYU Scientifica","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124223281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Over the years, the venoms of various animals have been found to include a variety of antibacterial compounds. One of the greatest challenges of public health is multidrug-resistant bacteria strains which always call for new and potent antibacterial agent to help curb these strains of bacteria. In the quest to source antibacterial agents active against multidrug-resistant bacteria, this research work was designed to investigate the antibacterial activity of crude venoms of B. arietans and N. nigricollis against gram-positive and gram-negative bacterial strains. Current studies revealed that Puff adder (Bitis arietans) of the Viperidae family crude venom showed distinct antibacterial activity against the clinical isolates and more efficient than (Naja nigricollis) of Elapidae family as well as tested antibiotics available today. The methods include antibacterial activity screening assay, followed by scanning electron microscope and molecular docking techniques. The minimum inhibitory concentration (MIC) for puff adder crude venom was 8 g/ml against Staphylococcus aureus ATCC. However, the MIC for common antibiotics (ampicillin, penicillin, chloramphenicol, and tetracycline) was in the range of 8-64 g/ml. The venom of the puff adder (Bitis arietans) exhibited antibacterial action against gram-positive bacteria through the cell wall and membrane damage, according to the results of scanning electron microscopy. The molecular docking established a mechanism of action between venom protein and the ligands in the cell wall of gram-positive bacteria. The result identified high docking energy scores and interacting amino acid residue. Puff adder (Bitis arietans) of the Viperidae family crude venom demonstrates a workable source for investigating antimicrobial prototypes for upcoming novel antibiotics against clinical microorganisms with medication resistance.
{"title":"Antibacterial Activity and Silico Molecular Prediction of Snake Venoms (Bitis arietans and Naja nigricollis) Against Some Clinical Bacterial Isolates","authors":"Muizz Sulaimon O., Binta Garba Kurfi, Sanusi Magaji, Olayele Gbenga Awujoola","doi":"10.56919/usci.1122.019","DOIUrl":"https://doi.org/10.56919/usci.1122.019","url":null,"abstract":"Over the years, the venoms of various animals have been found to include a variety of antibacterial compounds. One of the greatest challenges of public health is multidrug-resistant bacteria strains which always call for new and potent antibacterial agent to help curb these strains of bacteria. In the quest to source antibacterial agents active against multidrug-resistant bacteria, this research work was designed to investigate the antibacterial activity of crude venoms of B. arietans and N. nigricollis against gram-positive and gram-negative bacterial strains. Current studies revealed that Puff adder (Bitis arietans) of the Viperidae family crude venom showed distinct antibacterial activity against the clinical isolates and more efficient than (Naja nigricollis) of Elapidae family as well as tested antibiotics available today. The methods include antibacterial activity screening assay, followed by scanning electron microscope and molecular docking techniques. The minimum inhibitory concentration (MIC) for puff adder crude venom was 8 g/ml against Staphylococcus aureus ATCC. However, the MIC for common antibiotics (ampicillin, penicillin, chloramphenicol, and tetracycline) was in the range of 8-64 g/ml. The venom of the puff adder (Bitis arietans) exhibited antibacterial action against gram-positive bacteria through the cell wall and membrane damage, according to the results of scanning electron microscopy. The molecular docking established a mechanism of action between venom protein and the ligands in the cell wall of gram-positive bacteria. The result identified high docking energy scores and interacting amino acid residue. Puff adder (Bitis arietans) of the Viperidae family crude venom demonstrates a workable source for investigating antimicrobial prototypes for upcoming novel antibiotics against clinical microorganisms with medication resistance.","PeriodicalId":235595,"journal":{"name":"UMYU Scientifica","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126283199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sunday Ojogbane Agbo, Yemi-Peters Victoria Ifeoluwa, Adewumi Sunday Eric
The instability of Premium Motor Spirit (PMS/Petrol) and other energy commodities prices, occasioned by volatile and dynamic movement of prices has been found to affect the cost of production in Nigeria. As a result, this paper studies current literature on the applications of machine learning techniques in forecasting PMS (Petrol) and other energy commodities prices. The review has been done through an electronic search of the published papers in the last 4 years (2019-2022). A total number of twenty-nine (29) publications on PMS (Petrol) and other energy commodities prices forecasting using machine learning models were selected for the study to identify research gaps and future works. This paper covers a summary of reviewed published papers on forecasting PMS (Petrol) and other energy commodities prices using machine learning techniques, semantic analysis of algorithms used, and the taxonomy of the models adopted in the published papers. The results showed that there are studies that presented the application of machine learning models in forecasting the prices of PMS (Petrol) and other energy commodities in other countries. However, very few of them have proposed the construction of machine learning models for forecasting PMS (Petrol) and other energy commodities prices in Nigeria. This leads to the need to develop new models, especially deep learning hybrid models.
{"title":"Forecasting Premium Motor Spirit (PMS) and Energy Commodities Prices Using Machine Learning Techniques: A Review","authors":"Sunday Ojogbane Agbo, Yemi-Peters Victoria Ifeoluwa, Adewumi Sunday Eric","doi":"10.56919/usci.1122.025","DOIUrl":"https://doi.org/10.56919/usci.1122.025","url":null,"abstract":"The instability of Premium Motor Spirit (PMS/Petrol) and other energy commodities prices, occasioned by volatile and dynamic movement of prices has been found to affect the cost of production in Nigeria. As a result, this paper studies current literature on the applications of machine learning techniques in forecasting PMS (Petrol) and other energy commodities prices. The review has been done through an electronic search of the published papers in the last 4 years (2019-2022). A total number of twenty-nine (29) publications on PMS (Petrol) and other energy commodities prices forecasting using machine learning models were selected for the study to identify research gaps and future works. This paper covers a summary of reviewed published papers on forecasting PMS (Petrol) and other energy commodities prices using machine learning techniques, semantic analysis of algorithms used, and the taxonomy of the models adopted in the published papers. The results showed that there are studies that presented the application of machine learning models in forecasting the prices of PMS (Petrol) and other energy commodities in other countries. However, very few of them have proposed the construction of machine learning models for forecasting PMS (Petrol) and other energy commodities prices in Nigeria. This leads to the need to develop new models, especially deep learning hybrid models.","PeriodicalId":235595,"journal":{"name":"UMYU Scientifica","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115211822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Nababa, Mustapha Amadu Sadauki, Hadiza Yakubu Bako
A twelve month study was carried out between March 2020 and February 2021, to assess water quality parameters and fishermen catch per unit effort of Zobe reservoir in Katsina State, Nigeria with the aim of understanding the contamination position of water body and fishing effort. Five chosen sampling stations are; Raddawa, Tabobi, Gada, Garhi, and Makera. Selected physicochemical parameters such as temperature, pH, NH3, turbidity, alkalinity, BOD and alkalinity were assessed using standard methods. However, they were within all the recommended level for optimum performance of tropical fish species. Individual fishermen catch was used throughout the study period, where each of the five (5) Landing sites was visited twice monthly for catch assessment survey. Fish samples were randomly collected from 5 canoes/fishermen per sampling unit and catches were observed and recorded. There was high catch in the month of July and August (wet season) for all the species in Zobe reservoir. In contrary, there was strong negative correlation between temperature and DO; pH and DO; turbidity and DO; DO and BOD; DO and alkalinity. Makera had higher catches than any of the other stations with more than 700 bi-weekly catch representations between the months of July and August, 2020. Dry season CPUE was up to 22% for wet season and 9.80% for Clarias gariepinus in Garhi fishing station which recorded the highest, whilst for Clarias anguilaris CPUE recorded absolute zeros for all the stations and for both seasons except for Makera in wet season with 0.08% CPUE. Physicochemical parameters of Zobe reservoir showed that the water quality of Zobe reservoir changes with season, however, the parameters were within an acceptable range for fish growth and dependency of fish catch and water quality was observed.
2020年3月至2021年2月期间开展了一项为期12个月的研究，以评估尼日利亚卡齐纳州Zobe水库的水质参数和渔民单位捕捞量，目的是了解水体的污染位置和捕捞量。五个选定的采样站是;Raddawa, Tabobi, Gada, Garhi和Makera。选取物化参数，如温度、pH、NH3、浊度、碱度、BOD和碱度，采用标准方法进行评价。但是，它们都在热带鱼最佳生产性能的所有推荐水平之内。在整个研究期间，使用个体渔民的渔获量，每个月访问五个着陆点两次，进行渔获量评估调查。每个采样单位随机从5艘独木舟/渔民处采集鱼样，并观察和记录渔获量。7月和8月(丰水期)是Zobe水库所有种类的高捕获量。相反，温度与DO呈较强的负相关;pH和DO;浊度和DO;DO和BOD;DO和碱度。Makera的捕获量比其他任何一个站点都高，在2020年7月至8月期间，每两周有700多条捕捞记录。干季CPUE为22%，湿季最高，Garhi渔站的claras gariepinus最高，为9.80%，而Clarias anguilaris的CPUE在除Makera渔站外的所有渔站和两个渔站均为绝对零，湿季为0.08%。Zobe水库的理化参数表明，Zobe水库的水质随季节变化，但这些参数都在鱼类生长可接受的范围内，并且观察到渔获量与水质的依赖性。
{"title":"Water Quality and Catch Per Unit Effort (CPUE) of Fish Species in Zobe Reservoir, Dutsin-Ma, Nigeria","authors":"A. Nababa, Mustapha Amadu Sadauki, Hadiza Yakubu Bako","doi":"10.56919/usci.1122.030","DOIUrl":"https://doi.org/10.56919/usci.1122.030","url":null,"abstract":"A twelve month study was carried out between March 2020 and February 2021, to assess water quality parameters and fishermen catch per unit effort of Zobe reservoir in Katsina State, Nigeria with the aim of understanding the contamination position of water body and fishing effort. Five chosen sampling stations are; Raddawa, Tabobi, Gada, Garhi, and Makera. Selected physicochemical parameters such as temperature, pH, NH3, turbidity, alkalinity, BOD and alkalinity were assessed using standard methods. However, they were within all the recommended level for optimum performance of tropical fish species. Individual fishermen catch was used throughout the study period, where each of the five (5) Landing sites was visited twice monthly for catch assessment survey. Fish samples were randomly collected from 5 canoes/fishermen per sampling unit and catches were observed and recorded. There was high catch in the month of July and August (wet season) for all the species in Zobe reservoir. In contrary, there was strong negative correlation between temperature and DO; pH and DO; turbidity and DO; DO and BOD; DO and alkalinity. Makera had higher catches than any of the other stations with more than 700 bi-weekly catch representations between the months of July and August, 2020. Dry season CPUE was up to 22% for wet season and 9.80% for Clarias gariepinus in Garhi fishing station which recorded the highest, whilst for Clarias anguilaris CPUE recorded absolute zeros for all the stations and for both seasons except for Makera in wet season with 0.08% CPUE. Physicochemical parameters of Zobe reservoir showed that the water quality of Zobe reservoir changes with season, however, the parameters were within an acceptable range for fish growth and dependency of fish catch and water quality was observed.","PeriodicalId":235595,"journal":{"name":"UMYU Scientifica","volume":"310 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133469808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Suleiman, Dr. Nike Tawakaltu Isyaku, Dr. Ukatu Victoria E., Yusuf, Ibrahim Alhaji, Abubakar Hafiz
Over 200 million people are suffering from the debilitating schistosomiasis, which has the greatest morbidity and mortality rates in African nations. Schistosomiasis continues to be a tropical disease that receives little attention from governments and healthcare Institutions while having a wide range of negative impacts on society's health and socioeconomic hardship. The establishment of precise investigation for both gut and urinary schistosomiasis is one of the crucial areas that are severely undeveloped. A review was conducted to highlight immunological methods used to detect Schistosomiasis. Databases from ScienceDirect, World Health Organization, and PubMed were used. Articles for which at least the abstract was available in English were selected for the present study. Relevant articles were screened, duplicates were eliminated, eligibility standards were followed, and qualified studies were reviewed. Techniques including Skin Reaction Test/Biopsy, Indirect Immuno-Fluorescence Test (IFT), Indirect Hemagglutination Test (IHAT), Circumoval Precipitin Test (Copt), Monoclonal Antibodies Test (Mabt), ELISA, and others were discussed. The challenges faced by these techniques were also highlighted. Among the techniques discussed, ELISA was found to be the most widely used as it is the most effective, easy to use, and could detect both chronic and acute Schistosomiasis
{"title":"A Review on the Immunological Techniques Use for Detection of Schistosoma spp Infection","authors":"J. Suleiman, Dr. Nike Tawakaltu Isyaku, Dr. Ukatu Victoria E., Yusuf, Ibrahim Alhaji, Abubakar Hafiz","doi":"10.56919/usci.1122.039","DOIUrl":"https://doi.org/10.56919/usci.1122.039","url":null,"abstract":"Over 200 million people are suffering from the debilitating schistosomiasis, which has the greatest morbidity and mortality rates in African nations. Schistosomiasis continues to be a tropical disease that receives little attention from governments and healthcare Institutions while having a wide range of negative impacts on society's health and socioeconomic hardship. The establishment of precise investigation for both gut and urinary schistosomiasis is one of the crucial areas that are severely undeveloped. A review was conducted to highlight immunological methods used to detect Schistosomiasis. Databases from ScienceDirect, World Health Organization, and PubMed were used. Articles for which at least the abstract was available in English were selected for the present study. Relevant articles were screened, duplicates were eliminated, eligibility standards were followed, and qualified studies were reviewed. Techniques including Skin Reaction Test/Biopsy, Indirect Immuno-Fluorescence Test (IFT), Indirect Hemagglutination Test (IHAT), Circumoval Precipitin Test (Copt), Monoclonal Antibodies Test (Mabt), ELISA, and others were discussed. The challenges faced by these techniques were also highlighted. Among the techniques discussed, ELISA was found to be the most widely used as it is the most effective, easy to use, and could detect both chronic and acute Schistosomiasis","PeriodicalId":235595,"journal":{"name":"UMYU Scientifica","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129930909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Adepehin, F. F. Magi, O. R. Omokungbe, Temitayo Olajide, Adetayo Oluwaseun Olajide
Accurate shale volume estimation is an important approach in reservoirs characterization as it forms the basis upon which evaluators can ascertain the hydrocarbon content of the reservoirs. The porosity, gamma ray, neutron-density and deep induction logs data were used to arrive at suitable shale volume estimates of the field studied. Analysis of well logs data was done using the TECHLOG Exploration software. Delineation of reservoirs was carried out with OpendTect software. The Microsoft excel spreadsheet was utilized to accurately estimate other suitable petrophysical parameters such as the permeability, water saturation, hydrocarbon saturation and the porosity. Three different non-linear shale volume models, the Larionov, the Steiber and the Clavier models were used to determine the reservoirs’ shale content across three wells of Yewa reservoirs characterized by varying thicknesses. Variation in the depths down hole for each of the methods revealed that shale volume estimates with the Larionov model was determined across thickness 142.646 m with top and bottom depths of 1946.605 m and 2089.252 m respectively in well Y1, thicknes 90.678 m with top and bottom depths of 2164.690 m and 2255.368 m respectively in well Y2 and thickness 107.290 m with top and bottom depths of 2303.374 m and 2410.663 m respectively in well Y3. The estimates with Steiber model were respectively determined across thicknesses 85.649 m, 95.098 m and 121.371 m for Y1, Y2 and Y3 reservoirs, and top and bottom depths of 1947.571 m and 2033.219 m in well Y1, 2041.754 m and 2136.851 m in well Y2 and 2144.979 m and 2266.442 m in well Y3 and the one with Clavier model were respectively determined across thicknesses 146.456 m, 147.752 m and 94.869 m for Y1, Y2 and Y3 reservoirs and top and bottom depths of 1760.601 m and 1907.057 m in well Y1, 1920.312 m and 2068.068 m in well Y2 and 2078.812 m and 2173.681 m in well Y3. The lowest shale volume average estimate was recorded from the Larionov model. Nevertheless, one cannot conclude that the Larionov model is the most reliable as values obtained may be because of instability in the sensitivities of utilized well logs and the complexities in the properties of wells down hole. A further investigation of the sensitivities of the well logs and the down hole properties of the wells showed that the Larionov method gives reasonable, consistent, and repetitive intervals when compared with the Steiber and the Clavier models. The Larionov model is hereby recommended for use in the study area.
准确的页岩体积估算是储层表征的重要手段，是评价人员确定储层含烃量的基础。利用孔隙度、伽马射线、中子密度和深部感应测井数据，对所研究的油田进行了适当的页岩体积估算。测井数据分析使用TECHLOG Exploration软件完成。利用opendect软件进行储层圈定。利用Microsoft excel电子表格准确估计其他合适的岩石物性参数，如渗透率、含水饱和度、含烃饱和度和孔隙度。采用Larionov、Steiber和Clavier三种不同的非线性页岩体积模型，确定了叶华三口井不同厚度储层的页岩含量。各方法的井深变化表明:Y1井的厚度为142.646 m，顶底深度分别为1946.605 m和2089.252 m; Y2井的厚度为90.678 m，顶底深度分别为2164.690 m和2255.368 m; Y3井的厚度为107.290 m，顶底深度分别为2303.374 m和2410.663 m。Y1、Y2和Y3储层厚度分别为85.649 m、95.098 m和121.371 m, Y1井为1947.571 m和2033.219 m, Y2井为2041.754 m和2136.851 m, Y3井为2144.979 m和2266.442 m, Y1井为146.456 m、147.752 m和94.869 m，使用Steiber模型分别确定了Steiber模型和Clavier模型。Y1井为1760.601 m、1907.057 m, Y2井为1920.312 m、2068.068 m, Y3井为2078.812 m、2173.681 m。Larionov模型记录了最低页岩体积平均估计值。然而，我们不能断定Larionov模型是最可靠的，因为所得到的值可能是由于利用的测井曲线的敏感性不稳定以及井下井性质的复杂性。对测井曲线的敏感性和井的井下性质的进一步研究表明，与Steiber和Clavier模型相比，Larionov方法给出了合理、一致和重复的层段。因此，建议在研究区域使用Larionov模型。
{"title":"Assessment of Three Non-Linear Approaches of Estimating the Shale Volume Over Yewa Field, Niger Delta, Nigeria","authors":"D. Adepehin, F. F. Magi, O. R. Omokungbe, Temitayo Olajide, Adetayo Oluwaseun Olajide","doi":"10.56919/usci.1122.004","DOIUrl":"https://doi.org/10.56919/usci.1122.004","url":null,"abstract":"Accurate shale volume estimation is an important approach in reservoirs characterization as it forms the basis upon which evaluators can ascertain the hydrocarbon content of the reservoirs. The porosity, gamma ray, neutron-density and deep induction logs data were used to arrive at suitable shale volume estimates of the field studied. Analysis of well logs data was done using the TECHLOG Exploration software. Delineation of reservoirs was carried out with OpendTect software. The Microsoft excel spreadsheet was utilized to accurately estimate other suitable petrophysical parameters such as the permeability, water saturation, hydrocarbon saturation and the porosity. Three different non-linear shale volume models, the Larionov, the Steiber and the Clavier models were used to determine the reservoirs’ shale content across three wells of Yewa reservoirs characterized by varying thicknesses. Variation in the depths down hole for each of the methods revealed that shale volume estimates with the Larionov model was determined across thickness 142.646 m with top and bottom depths of 1946.605 m and 2089.252 m respectively in well Y1, thicknes 90.678 m with top and bottom depths of 2164.690 m and 2255.368 m respectively in well Y2 and thickness 107.290 m with top and bottom depths of 2303.374 m and 2410.663 m respectively in well Y3. The estimates with Steiber model were respectively determined across thicknesses 85.649 m, 95.098 m and 121.371 m for Y1, Y2 and Y3 reservoirs, and top and bottom depths of 1947.571 m and 2033.219 m in well Y1, 2041.754 m and 2136.851 m in well Y2 and 2144.979 m and 2266.442 m in well Y3 and the one with Clavier model were respectively determined across thicknesses 146.456 m, 147.752 m and 94.869 m for Y1, Y2 and Y3 reservoirs and top and bottom depths of 1760.601 m and 1907.057 m in well Y1, 1920.312 m and 2068.068 m in well Y2 and 2078.812 m and 2173.681 m in well Y3. The lowest shale volume average estimate was recorded from the Larionov model. Nevertheless, one cannot conclude that the Larionov model is the most reliable as values obtained may be because of instability in the sensitivities of utilized well logs and the complexities in the properties of wells down hole. A further investigation of the sensitivities of the well logs and the down hole properties of the wells showed that the Larionov method gives reasonable, consistent, and repetitive intervals when compared with the Steiber and the Clavier models. The Larionov model is hereby recommended for use in the study area.","PeriodicalId":235595,"journal":{"name":"UMYU Scientifica","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127610325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I have studied the role of lattice connectivity and coupling weights distribution on the entanglement of quantum spin-glasses. It's found in this work that the connectivity of the lattice weakly influence the degree of entanglement in the spin-glass compared to the distribution of the coupling constants between the spins. This suggest important implications for machine learning models such as Boltzmann machines and the study of complex quantum systems.
{"title":"Lattice connectivity and entanglement in quantum spin-glasses","authors":"Y. Ibrahim","doi":"10.56919/usci.1122.042","DOIUrl":"https://doi.org/10.56919/usci.1122.042","url":null,"abstract":"I have studied the role of lattice connectivity and coupling weights distribution on the entanglement of quantum spin-glasses. It's found in this work that the connectivity of the lattice weakly influence the degree of entanglement in the spin-glass compared to the distribution of the coupling constants between the spins. This suggest important implications for machine learning models such as Boltzmann machines and the study of complex quantum systems.","PeriodicalId":235595,"journal":{"name":"UMYU Scientifica","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132868812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Traditional sampling methods such as the Monte Carlo method are computationally expensive and not feasible for studying large and complex systems. These methods are essential for developing new materials, optimizing chemical reactions, and understanding biological processes. However, simulating thermodynamic systems for physically relevant system sizes is computationally challenging. This is partly due to the exponential growth of the configuration space with the system size. With the current Monte Carlo methods, studying the same system for different investigation of its properties means repeating the expensive computation multiple times. In this article, I showed that thermodynamic systems can be sampled using a surrogate neural network model thereby avoiding the computationally expensive proposal Monte Carlo methods for subsequent investigations. To demonstrate the method, I trained a feed-forward neural network surrogate for the Boltzmann distribution of the Ising model. This approach would potentially help accelerate Monte Carlo simulations towards understanding the physics of novel materials and some biological processes.
{"title":"Sampling thermodynamic systems with neural network surrogates","authors":"Y. Ibrahim","doi":"10.56919/usci.1122.043","DOIUrl":"https://doi.org/10.56919/usci.1122.043","url":null,"abstract":"Traditional sampling methods such as the Monte Carlo method are computationally expensive and not feasible for studying large and complex systems. These methods are essential for developing new materials, optimizing chemical reactions, and understanding biological processes. However, simulating thermodynamic systems for physically relevant system sizes is computationally challenging. This is partly due to the exponential growth of the configuration space with the system size. With the current Monte Carlo methods, studying the same system for different investigation of its properties means repeating the expensive computation multiple times. In this article, I showed that thermodynamic systems can be sampled using a surrogate neural network model thereby avoiding the computationally expensive proposal Monte Carlo methods for subsequent investigations. To demonstrate the method, I trained a feed-forward neural network surrogate for the Boltzmann distribution of the Ising model. This approach would potentially help accelerate Monte Carlo simulations towards understanding the physics of novel materials and some biological processes.","PeriodicalId":235595,"journal":{"name":"UMYU Scientifica","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117128301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fibre-filled high-density polyethylene composite was prepared by two roll melt mixing, and pressed into standard shapes using compression moulding technique for varying fibre contents from 10% by weight up to 60w% by weight. Tests were performed on composite specimens in accordance with ASTM D638. Additives have been incorporated into the design formulation of the composite to provide flexibility and intercalate (adhesion) between the fibre and the substrate. The results obtained were compared with specimens made of 100% weight of high-density polyethylene (HDPE). Results showed that waste loads in the range of 10-40% weight for un-treated hides (UH) and plant treated cowhide (acacia nilotical) (VT), represent good mechanical, physical, thermal and morphological properties, with improved intercalation between the fibre and interface substrate due to additives. 10-40 % weight (non-degradable) HDPE can be partially replaced with rawhide and processed shredded hide (both compostable), with the highest value at 10% by weight fibre content. The breaking strength of high-density polyethylene filled untreated hide with additive (HDPE/UHA) and high-density polyethylene filled plant treated hide with additives (HDPE/VTA) stretches longer under tension by 32.7% and 3.9% respectively, more than the control at 40% content by weight. The composites are suitable for producing composite-films, useful for manufacturing bags for packaging food goods, or in shoe soles, floor tiles and any material property requiring flexibility.
{"title":"Effect of Additives on the flexibility of High-Density Polyethylene Filled Cowhide Composite","authors":"Musa, Esther Turu, Hamza, Abba, Ahmed, Abdulkarim Salawu, Ishiaku, Umaru Semo, Yerima, Yakubu","doi":"10.56919/usci.1122.014","DOIUrl":"https://doi.org/10.56919/usci.1122.014","url":null,"abstract":"Fibre-filled high-density polyethylene composite was prepared by two roll melt mixing, and pressed into standard shapes using compression moulding technique for varying fibre contents from 10% by weight up to 60w% by weight. Tests were performed on composite specimens in accordance with ASTM D638. Additives have been incorporated into the design formulation of the composite to provide flexibility and intercalate (adhesion) between the fibre and the substrate. The results obtained were compared with specimens made of 100% weight of high-density polyethylene (HDPE). Results showed that waste loads in the range of 10-40% weight for un-treated hides (UH) and plant treated cowhide (acacia nilotical) (VT), represent good mechanical, physical, thermal and morphological properties, with improved intercalation between the fibre and interface substrate due to additives. 10-40 % weight (non-degradable) HDPE can be partially replaced with rawhide and processed shredded hide (both compostable), with the highest value at 10% by weight fibre content. The breaking strength of high-density polyethylene filled untreated hide with additive (HDPE/UHA) and high-density polyethylene filled plant treated hide with additives (HDPE/VTA) stretches longer under tension by 32.7% and 3.9% respectively, more than the control at 40% content by weight. The composites are suitable for producing composite-films, useful for manufacturing bags for packaging food goods, or in shoe soles, floor tiles and any material property requiring flexibility.","PeriodicalId":235595,"journal":{"name":"UMYU Scientifica","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127651998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alhaji Modu Isa, Sule Omeiza Bashiru, Alhaji Buhari Ali, Akeem Ajibola Adepoju, Ibrahim Ismaila Itopa
To increase flexibility or to develop covariate models in various ways, new parameters can be added to existing families of distributions or a new family of distributions can be compounded with well-known standard normal distribution. In this paper, a trigonometric-type distribution was developed in order to come up with flexible distribution without adding parameters, considering Exponential distribution as the baseline distribution and Sine-G as the generator. The proposed distribution is referred to as Sine Exponential Distribution. Statistical features, including the moment, moment generating function, entropy, and order statistics were obtained. The proposed distribution's parameters were estimated using the Maximum Likelihood method. Using real datasets, the model's importance was demonstrated. The newly developed model was proven to be better than its competitors.
{"title":"Sine-Exponential Distribution: Its Mathematical Properties and Application to Real Dataset","authors":"Alhaji Modu Isa, Sule Omeiza Bashiru, Alhaji Buhari Ali, Akeem Ajibola Adepoju, Ibrahim Ismaila Itopa","doi":"10.56919/usci.1122.017","DOIUrl":"https://doi.org/10.56919/usci.1122.017","url":null,"abstract":"To increase flexibility or to develop covariate models in various ways, new parameters can be added to existing families of distributions or a new family of distributions can be compounded with well-known standard normal distribution. In this paper, a trigonometric-type distribution was developed in order to come up with flexible distribution without adding parameters, considering Exponential distribution as the baseline distribution and Sine-G as the generator. The proposed distribution is referred to as Sine Exponential Distribution. Statistical features, including the moment, moment generating function, entropy, and order statistics were obtained. The proposed distribution's parameters were estimated using the Maximum Likelihood method. Using real datasets, the model's importance was demonstrated. The newly developed model was proven to be better than its competitors.","PeriodicalId":235595,"journal":{"name":"UMYU Scientifica","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130317549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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