bluuebunny/crossref_metadata_2025 huggingface dataset:
Automation and Labour in India: Policy Implications of Job Polarisation pre and post COVID-19 crisis
Authors: Nippani Abishek
Published: August 2020

Advancements in ICTs have heightened the potential of such technology to automate jobs and render labour redundant en masse, uniting the concerns of sociologists, policy makers, and economists alike. Realistically, however, concern revolves not around redundancy of labour, but the polarising effect automation exerts on jobs. This polarisation stems from the claim that automation 'hollows out' mid-skill jobs, thereby increasing demand for high- and low- skill jobs. Job polarisation widens wage disparity, lowers the aggregate skill level of labour and exacerbates existing social inequalities. Proponents of laissez-faire automation argue that while automation may exert adverse effects on labour in the short run, it is bound to realise higher net benefits and employment in the long run. Such an understanding which is based on the Schumpterian notion of creative destruction is predicated on the fact that firms would adopt only such technology which bring about substantial strides in productivity. However, world over and in India firms have been merely substituting labour with capital, without any greater efficiency gains. This trend is only set to worsen with the ongoing health crisis due to varied reasons. In such a situation, it becomes imperative to design novel methods of social security.
Developing a Web Based Decision Support System for Disaster Management on Aila Affected Area of Koyra Upazila
Authors: Ahasan Rakibul , Saimon Sajadul Alam
Published: August 2020

Bangladesh is one of the most disaster prone countries of the world and has been subjected to frequent natural disasters in many forms, particularly cyclonic storms and storm surges. The low-lying coastal areas are particularly vulnerable, thus placing these population, infrastructure, agriculture, livestock and economic development in a high-risk situation. The situation calls for an effective cyclone warning and dissemination system. With a view to address that this research intends to develop and manage a website containing all the information for helping in taking decision about disaster management. As its common knowledge that disaster victims need immediate, efficient and effective rescue and relief services, this system will provide relief and rescue workers with a platform easy to use, fast to search, retrieve and access information and most importantly will help in preventing the duplication of relief works. Overall, proper co-ordination will be ensured among the existing organization seems to be lacking due to the shortage of effective information dissemination system.
COMMUNITY BASED APPROACH FOR SOLID WASTE MANAGEMENT IN KHULNA CITY
Authors: Ahasan Rakibul
Published: August 2020

Generation of solid waste (SW) is a major problem in urban areas, thus its management is one of the important obligatory functions to not only urban local authority but also for the inhabitants. The citizens expressed their concerns about the waste management system in KCC and associated problems that they are encountering. Waste generation in Khulna City Corporation is around 455 tons of municipal solid waste/day and generation rate is now 0.75 Kg/capita/day on an average. Existing public utility services and facilities are not adequate to meet the demand of disposing these massive amounts of wastes and that’s why several problems are arising. There are some deterrents in the KCC’s solid waste Management system, arising from both the city corporation authority and the citizen of different levels. With a view to address the problem from through community participation, this paper intends to evaluate the potential of community based solid waste management approach in context of Khulna city.
Valuation of Reliability Index in Distribution Network 13.8 kV
Authors: Yaser F. , Zakri Azriyenni Azhari , Sukma D. Y.
Published: August 2020

This study is proposed to calculate and analyze the level of reliability of the 13.8 kV distribution system. To calculate the reliability index based on the reliability index of the value of the failure that occurred. The method used throughout this study is the Reliability Index Assessment (RIA) when this method takes into account momentary interruption. The distribution network is considered as the object of this study has six feeders. Based on blackout data obtained, the reliability index becomes smaller and can be distinguished between permanent and temporary disruptions. The calculation results show the reliability index of SAIDI, SAIDI, and MAIFI based on the type of disturbance; the results of this calculation will be compared with SPLN and IEEE. A comparison of the results of the calculation of SAIFI values from the six feeders analyzed all meet the SPLN and IEEE rules. However, in one of the feeders, the SAIDI index exceeds the established standard, which is 24 hours/year/customer, with the SPLN regulation being 21 hours/year/customer, and the IEEE standard is 2.3 hours/customer/year. And finally, the results of an analysis of the MAIFI index for all feeders meet the IEEE standard of 5 times/year/customers.
PERLINDUNGAN HUKUM TERHADAP PEJABAT PEMBUAT KOMITMEN (PPK) DALAM PENGADAAN BARANG/JASA PEMERINTAH PADA SISTEM PENGADAAN SECARA ELEKTRONIK
Authors: Kristiani Mita
Published: August 2020

Legal protection or legal assistance for government procurement of goods services is actually regulated  in relevant laws and regulations, but what kind of protection has not been explained and regulated in detail in the laws and regulations. Due to the absence of a rule that regulates explicitly and clearly related to the protection of actors in the procurement of government goods/services and the lack of attention from the government. So based on this, the thing offered is the need to make a policy that regulates clearly and completely related to the protection of government procurement of goods/services.Keywords: Procurement of Government Services, Commitment Making Officer, Legal protection
IMPLEMENTASI PELAYANAN KESEHATAN MENURUT UNDANG-UNDANG NO. 24 TAHUN 2011 TENTANG BADAN PENYELENGGARA JAMINAN SOSIAL (BPJS) (Studi di RSUD Kertosono Kabupaten Nganjuk)
Authors: Meutia Binar Idha
Published: August 2020

The purpose of this study was to analyze BPJS Health services in Kertosono District Hospital Nganjuk District, and to analyze the supporting and inhibiting factors of BPJS Health services in Kertosono District Hospital Nganjuk Regency. The results of this study are: First, health services in Kertosono Regional Hospital Nganjuk said to be very good, it is because of the commitment of the Kertosono Regional Hospital who want to provide health services according to good standards and based on public service standards to the community. Second, the supporting factors in providing services to patients are, the attitude of employees who are friendly and polite, the services provided are satisfactory and the flow is easy, there are poster announcements related to BPJS, clear goals and objectives, and sufficient financial. The inhibiting factors of HR owned by hospitals are not comparable to those treated (patients), frequent miscommunication between officers and patients, incomplete medical devices, inefficiency of the BPJS claim process, and arrears of payment from the BPJS.Keywords: Services, Health, Badan Penyelenggara Jaminan Sosial (BPJS)
Tecnologías para luchar contra la pandemia Covid-19: geolocalización, rastreo, big data, SIG, inteligencia artificial y privacidad
Authors: Cascón-Katchadourian Jesús-Daniel
Published: August 2020

Many applications and websites to fight the Covid-19 pandemic have been created and developed in recent months by both official institutions and commercial or private initiatives. A large number of projects that use technologies such as geolocation, geopositioning, geofencing, tracking, and registration of contacts through Bluetooth have arisen, generating a huge amount of data. By using big data techniques, geographic information systems (GIS), and artificial intelligence, information has been produced for health institutions and society itself, helping to address the health crisis more efficiently. This article describes, analyzes, and offers a systematized review of a significant sample of websites and applications recently implemented successfully or under development by public and private institutions. We searched the available scholarly literature, as well as news from the main newspapers, websites, and digital media specialized in technology. The article concludes with a description of the best and most efficient practices found, relating then to the right to privacy and personal data protection.

Resumen
La creación y desarrollo en los últimos meses de aplicaciones y webs para luchar contra la pandemia de la Covid-19, tanto de instituciones oficiales como iniciativas empresariales o particulares, ha sido importante. Han surgido un gran número de proyectos que usan tecnologías como geolocalización, geoposicionamiento, geofencing, rastreo y registro de contactos a través de bluetooth, para generar una ingente cantidad de datos. Mediante técnicas de análisis de datos masivos (big data), sistemas de información geográfica (SIG) e inteligencia artificial se ha producido información para las instituciones sanitarias y para la propia sociedad, ayudando así a afrontar de manera más eficiente la crisis sanitaria. El presente artículo describe, analiza y ofrece la revisión sistematizada de una muestra significativa de webs y aplicaciones implementadas recientemente con éxito o en desarrollo, por parte de instituciones públicas y privadas. Se ha buscado la bibliografía científica disponible, así como las noticias de los principales periódicos, webs y medios digitales especializados en tecnología. El artículo concluye con una descripción de las mejores y más eficientes prácticas encontradas, poniéndolas en relación con el derecho a la privacidad y la protección de los datos personales.
A new species of the genus Campsicnemus (Diptera: Dolichopodidae) from Kyrgyzstan
Authors: Selivanova O.V. , Negrobov O.P. , Grichanov I.Ya.
Published: August 2020

A new species Campsicnemus issykkulensis sp. nov. is described from Kyrgyzstan. It belongs to the C. magius group of species, being similar to C. compeditus Loew, 1857 and C. bagachanovae Grichanov et Volfov, 2009, and differs from these latter mainly in morphology of the male fore tarsus.
The Right to Silence in the EU Directive 2016/343 on the Strengthening of Certain Aspects of the Presumption of Innocence from the Perspective of Polish Criminal Proceedings
Authors: Sakowicz Andrzej
Published: August 2020

The right to remain silent is one of the most fundamental principles of domestic and international criminal law. It’s is also closely related to the presumption of innocence. As the responsibility is placed on the prosecution to prove the guilt of a person it follows that the accused should not be forced to assist the prosecution by being forced to speak. The right to remain silent expresses the individual’s right not to be compelled to testify against himself or to confess guilt. Its core component is the freedom to choose whether or not  to give answers to individual questions or to provide explanations. To use against the suspected silence under police questioning and his refusal to testify during trial amounted to subverting the presumption of innocence and the onus of proof resulting from that presumption: it is for the prosecution to prove the accused’s guilt without any assistance from the latter being required. This article has to objectives. Firstly, to interpret the right to remain silent in the light to of the Directive 2016/343 on the strengthening of certain aspects of the presumption of innocence and of the right to be present at the trial in criminal proceeding. Secondly, the  Directive 2016/343 can be used as reference to evaluate a degree to which Polish legal solutions conform to the Directive in question, giving rise to several postulates  in  that  matter. The analysis will also include shortages and problems resulting from imperfect Polish criminal process in that field.
Evaluation of the endocarp and epicarp extract of Cereus fricii cactus as a carbon steel corrosion inhibitor
Authors: García Guzmán Ana , Meza Castellar Pedro , Tejada Tovar Candelaria , Villabona Ortiz ´Ángel , Acevedo Correa Diofanor
Published: August 2020

Se utilizaron extractos de Endocarpio y pericarpio de cactus Cereus fricii para inhibir la corrosión del acero al carbono en soluciones de HCl y NaCl mediante ensayos gravimétricos. Los extractos fueron obtenidos mecánicamente, las concentraciones fueron fijadas y caracterizadas por pruebas fitoquímicas y análisis FTIR y la naturaleza de la inhibición fue determinada por cálculo de Gibbs Free Energy. Se estableció que los extractos tienen la presencia de taninos, saponinas y compuestos antioxidantes, lo que fue corroborado por el análisis FTIR, mostrando picos de absorbancia correspondientes a los grupos OH y COOH, siendo el extracto de endocarpio el de mayor proporción. Los extractos de endocarpio con una concentración del 5% mostraron un mejor rendimiento en la inhibición de la corrosión que los extractos obtenidos del epicarpio, con porcentajes del 97,71 al inhibir el HCl y del 73,91% al inhibir el NaCl. La presencia de taninos, saponinas y compuestos antioxidantes en los extractos del endocarpio y del epicarpio favorecen la inhibición de la corrosión metálica.
STUDY OF GELATIN FROM DUCK BONE AS AN ALTERNATIVE SOURCES OF HALAL GELATIN
Authors: Khirzin Muhammad Habbib
Published: August 2020

Gelatin is an intermediate ingredient which is oftenly used in many field such as food, pharmacy, and cosmetics. It is usually extracted from pig and cow. Halal issue of gelatin sources and the outbreaks of mad cow diseases encouraged people to find an alternative sources of gelatin. One of the alternative sources of gelatin was duck bone. The aim of this research was to describe physicochemical properties of duck bone gelatin which is extracted by using acid extraction method as an alternative sources of halal gelatin. The extraction of duck bone gelatin used 5% concentration of HCl (hydrochloric acid). The extraction process consisted of four steps, they were degreassing, defating, demineralization, and acid extraction. The result showed that gelatin which was extracted from duck bone had these several characteristic: yield of 6.24%, pH 4.0, water content of 13.43%, ash content of 13.42%, protein content of 65.43%, and whiteness degree of 30.35%. Generally, gelatin which was extracted from duck bone had similar characteristic with commercial gelatin and SNI standard. Further researcher had been suggested to reoptimized extraction method in order to reduce ash content.
Grenzen des Demokratielabors. Wie wahrscheinlich ist eine Parlamentskooperation von CDU und AfD in Ostdeutschland?
Authors: Höhne Benjamin
Published: August 2020

Wie realistisch wäre ein Bündnis aus CDU und AfD in ostdeutschen Landtagen? Abgewogen werden verschiedene Pro- und Kontra-Argumente, auch mittels Daten einer Parteimitgliederstudie. Eine Vereinnahmungsstrategie von CDU gegenüber AfD wäre hochriskant, weil sie nicht aus einer Position der Stärke geführt werden könnte.
Energiewendepolitik. Aufgaben, Probleme und Konflikte
Authors: Czada Roland
Published: August 2020

Die Energiewende ist eine Jahrhundertaufgabe. Sie setzt eine Politikwende voraus. Dabei geht es nicht nur um den Zubau von Windrädern und Solaranlagen. Größere Herausforderungen bestehen im Umbau weiter Teile der Wirtschaft, großtechnischer Infrastruktursysteme, des Arbeitsmarktes und in der Herausbildung neuer Lebensweisen. Sie stellen Politik, Wirtschaft und Gesellschaft vor vielfältige und komplexe Aufgaben, die in Deutschland bislang nicht zielführend gemeistert wurden.
Which remote ischemic preconditioning protocol is favorable in renal ischemia-reperfusion injury in the rat?
Authors: Varga Gabor , Ghanem Souleiman , Szabo Balazs , Nagy Kitti , Pal Noemi , Tanczos Bence , Somogyi Viktoria , Barath Barbara , Deak Adam , Matolay Orsolya , Bidiga Laszlo , Peto Katalin , Nemeth Norbert
Published: August 2020

BACKGROUND: The optimal timing of remote ischemic preconditioning (RIPC) in renal ischemia-reperfusion (I/R) injury is still unclear. We aimed to compare early- and delayed-effect RIPC with hematological, microcirculatory and histomorphological parameters. METHODS: In anesthetized male CrI:WI Control rats (n = 7) laparotomy and femoral artery cannulation were performed. In I/R group (n = 7) additionally a 45-minute unilateral renal ischemia with 120-minute reperfusion was induced. The right hind-limb was strangulated for 3×10 minutes (10-minute intermittent reperfusion) 1 hour (RIPC-1 group, n = 7) or 24 hour (RIPC-24 group, n = 6) prior to the I/R. Hemodynamic, hematological parameters and organs’ surface microcirculation were measured. RESULTS: Control and I/R group had the highest heart rate (p < 0.05 vs base), while the lowest mean arterial pressure (p < 0.05 vs RIPC-1) were found in the RIPC-24 group. The highest microcirculation values were measured in the I/R group (liver: p < 0.05 vs Control). The leukocyte count increased in I/R group (base: p < 0.05 vs Control), also this group’s histological score was the highest (p < 0.05 vs Control). The RIPC-24 group had a significantly lower score than the RIPC-1 (p = 0.0025 vs RIPC-1). CONCLUSION: Renal I/R caused significant functional and morphological, also in the RIPC groups. According to the histological examination the delayed-effect RIPC method was more effective.
The impact of organizational learning culture, workforce diversity and knowledge management on innovation and organization performance: A structural equation modeling approach
Authors: Khan Muhammad Shahid , Saengon Poramet , Charoenpoom Suppara , Soonthornpipit Hathaipan , Chongcharoen Duangkamol
Published: August 2020

BACKGROUND: Innovation is founded as a strong contributor to the formulation of competitive strategy and enhance organizational performance. Different organizations dropped drastically from the competition by not innovating their products and services. PURPOSE: To analyze the relationship of an organizational learning culture, workforce diversity and knowledge management with innovation and organizational performance, this topic is also has become an important topic in the field of management. With a few exceptions, however, the literature has focused on different business and small and medium-size enterprise, but this study intends to bridge this gap by testing the framework in educational institutes. METHODS: A quantitative research method is used to test the conceptual framework. The data was collected from Malaysian, and Thailand private sector universities; a closed-ended questionnaire was administrated to collect the data. Data is analyzed through statistical software SMART-PLS RESULTS: Findings of the study reveal that the exogenous variables knowledge management, organization learning culture, and workforce diversity has a significant and positive relationship with endogenous variable innovation and further innovation has a significant and positive association with organization performance. CONCLUSION: This study reveals that workforce diversity, knowledge management and organizational learning culture play a vital role to bring the innovation which further enhances the organization performance. Due to current pandemic COVID-19, educational institutes required more innovative process of teaching and operation, a learning culture, knowledge management systems and diverse workforce can play a vital role in the educational institute innovation process.
Modeling the Cognitive Trajectory in CADASIL
Authors: Brice Sandrine , Jabouley Aude , Reyes Sonia , Machado Carla , Rogan Christina , Dias-Gastellier Nathalie , Chabriat Hugues , du Montcel Sophie Tezenas
Published: August 2020

Background: For developing future clinical trials in Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), it seems crucial to study the long-term changes of cognition. Objective: We aimed to study the global trajectory of cognition, measured by the Mini-Mental State Examination (MMSE) and the Mattis Dementia Rating Scale (MDRS), along the course of CADASIL. Methods: Follow-up data of 185 CADASIL patients, investigated at the French National Referral center CERVCO from 2003, were considered for analysis based on strict inclusion criteria. Assuming that the MMSE and the MDRS provide imprecise measures of cognition, the trajectory of a common cognitive latent process during follow-up was delineated using a multivariate latent process mixed model. After adjustment of this model for sex and education, the sensitivities of the two scales to cognitive change were compared. Results: Analysis of the cognitive trajectory over a time frame of 60 years of age showed a decrease of performances with aging, especially after age of 50 years. This decline was not altered by sex or education but patients who graduated from high school had a higher mean cognitive level at baseline. The sensitivities of MMSE and MDRS scales were similar and the two scales suffered from a ceiling effect and curvilinearity. Conclusion: These data support that cognitive decline is not linear and mainly occurs after the age of 50 years during the course of CADASIL. They also showed that MMSE and MDRS scales are hampered by major limitations for longitudinal studies.
BACE1 and Other Alzheimer’s-Related Biomarkers in Cerebrospinal Fluid and Plasma Distinguish Alzheimer’s Disease Patients from Cognitively-Impaired Neurosyphilis Patients
Authors: Zhang Min , Zhong Xiaomei , Shi Haishan , Vanmechelen Eugeen , De Vos Ann , Liu Sen , Chen Ben , Mai Naikeng , Peng Qi , Chen Xinru , Wu Zhangying , Hou Le , Zhou Huarong , Ouyang Cong , Zhang Weiru , Liang Wanyuan , Dai Chunying , Ning Yuping
Published: August 2020

Background: Patients with spirochetal infection, which causes neurosyphilis (NS) and at a later stage general paresis of the insane (GPI), present with brain pathology features of Alzheimer’s disease (AD). However, the relationships among these illnesses regarding biomarker levels are still unclear. Objective: To explore biomarker levels in NS and GPI compared with those in AD and the relationship between biomarker levels and cognitive function in NS and GPI. Methods: Levels of neurogranin (NGRN) and β-amyloid precursor protein cleaving enzyme (BACE1) in cerebrospinal fluid (CSF)/plasma, together with amyloid-β 1–40 (Aβ40), Aβ42, and total tau in the CSF of 23 AD patients, 55 GPI patients, and 13 NS patients were measured. Patients were classified into none-to-mild, moderate, and severe stages of cognitive impairment. Results: Levels of CSF NGRN, BACE1, and tau as well as plasma BACE1 levels were significantly different among groups. In the none-to-mild stage, plasma BACE1 levels correlated with the protein levels in CSF and were significantly increased in AD patients versus GPI patients. The CSF tau levels in AD patients were significantly increased versus GPI patients in the moderate and severe stages. Pooling data from GPI and NS patients, both CSF tau and plasma NGRN levels correlated with cognitive scale scores. Conclusion: GPI and NS patients might have different biomarker level patterns compared to AD patients. While plasma BACE1 could be a promising early biomarker for distinguishing AD from GPI, CSF tau and plasma NGRN levels might be valuable in indications of cognitive function in pooled NS populations.
Fatty Acid-Binding Protein 3 in Cerebrospinal Fluid of Hip Fracture Patients with Delirium
Authors: Neerland Bjørn Erik , Halaas Nathalie Bodd , Idland Ane Victoria , Henjum Kristi , Blennow Kaj , Zetterberg Henrik , Watne Leiv Otto
Published: August 2020

Background: Delirium is associated with dementia and thus biomarkers reflecting neurodegeneration are of interest. Fatty acid-binding protein 3 (FABP3) is a cytoplasmic neuronal protein that has been isolated from the brain. It is released following brain injury and concentrations in cerebrospinal fluid (CSF) are also higher in neurodegenerative disorders such as Alzheimer’s disease (AD). Objective: To examine the relationship between CSF FABP3 concentration and delirium in hip fracture patients compared to a group of cognitively normal controls. Methods: CFS FABP3 concentration was measured in 128 hip fracture patients with (n = 71) and without (n = 57) delirium, and in cognitively unimpaired adults ≥64 years (n = 124) undergoing elective surgery. Results: CSF FABP3 (pg/ml) concentration (median (IQR)) was higher in hip-fracture patients compared to cognitively normal controls (5.7 (4.2–7.7) versus 4.5 (3.4–6.1), p < 0.001). There was a significant weak correlation between age and CSF FABP3 (ρ= 0.3, p < 0.001). After adjustment for age, the association between CSF FABP3 and hip-fracture was no longer statistically significant (β= 0.05, p = 0.5). There were no significant differences in CSF FABP3 concentration between hip fracture patients with (5.4 (4.1–8.2)) and without (5.8 (4.2–7.2)) delirium. CSF FABP3 concentration correlated positively with CSF AD biomarkers p-tau (ρ= 0.7, p < 0.01) and t-tau (ρ= 0.7, p < 0.01). Conclusion: CSF FABP3 concentrations were higher in hip fracture patients compared with cognitively normal older adults, indicating ongoing age-related neurodegeneration in these patients. There were no differences of CSF FABP3 concentrations across delirium groups, suggesting that neuronal damage or degeneration reflected by FABP3 may not be directly linked to delirium pathophysiology.
Ethnoracial Differences in Lewy Body Diseases with Cognitive Impairment
Authors: Kurasz Andrea M. , Smith Glenn E. , McFarland Maria G. , Armstrong Melissa J.
Published: August 2020

Background: Increasing research focuses on ethnic differences in Alzheimer’s disease, but such efforts in other neurodegenerative dementias are lacking. Currently, data on the ethnic profile of cognitively impaired persons with Lewy body disease (LBD) is limited, despite Lewy body dementia being the second most common neurodegenerative dementia. Objective: The study aimed to investigate presenting characteristics among ethnoracially diverse individuals with cognitive impairment secondary to LBD using the National Alzheimer’s Coordinating Center database. Methods: Participants self-identified as African American, Hispanic, or White. We used Kruskal-Wallis and Pearson χ2 analyses to investigate group differences in presenting characteristics and linear regression to compare neuropsychological test performance. Results: Presentation age was similar between groups (median 74–75 years). Compared to Whites (n = 1782), African Americans (n = 130) and Hispanics (n = 122) were more likely to be female and single, have less educational attainment, report more cardiovascular risk factors, describe less medication use, and perform worse on select cognitive tests. Hispanics reported more depressive symptoms. Conclusion: Cohorts differences highlight the need for population-based LBD studies with racial-ethnic diversity. Culturally-sensitive neuropsychological tests are needed to determine whether observed differences relate to cultural, social, testing, or disease-related factors. More research is needed regarding how social and biological factors impact LBD care among diverse populations.
Normal Pressure Hydrocephalus in Down Syndrome: The Report of Two Cases
Authors: Marano Massimo , Pompucci Angelo , Motolese Francesco , Rossi Mariagrazia , Coletta Ernesto , Di Lazzaro Vincenzo , Fasano Alfonso , Petrella Gianpaolo
Published: August 2020

Down syndrome (DS) is the most common cause of intellectual disability in infants and has a well-known relationship with the Alzheimer’s disease. The association between DS and the other pathologies of senescence, such as normal pressure hydrocephalus (NPH), has been poorly investigated. This series included two DS patients with NPH. In both cases, NPH symptoms were initially misdiagnosed as DS associated senescence. Patients were treated with ventricular-peritoneal shunt, showing a sustained improvement (1 and 4 years of follow-up). To our knowledge, this is the first description of the occurrence of NPH in adult patients with DS and surgical outcomes.
Potentially Pathogenic Calcium Oxalate Dihydrate and Titanium Dioxide Crystals in the Alzheimer’s Disease Entorhinal Cortex
Authors: Heller Adam , Coffman Sheryl S. , Jarvis Karalee
Published: August 2020

Knowing that Alzheimer’s disease (AD) nucleates in the entorhinal cortex (EC), samples of 12 EC specimens were probed for crystals by a protocol detecting fewer than 1/5000th of those present. Of the 61 crystals found, 31 were expected and 30 were novel. Twenty-one crystals of iron oxides and 10 atherosclerosis-associated calcium pyrophosphate dihydrate crystals were expected and found. The 30 unexpected crystals were NLRP3-inflammasome activating calcium oxalate dihydrate (12) and titanium dioxide (18). Their unusual distribution raises the possibility that some were of AD origination sites.
Independent and Correlated Role of Apolipoprotein E ɛ4 Genotype and Herpes Simplex Virus Type 1 in Alzheimer’s Disease
Authors: Zhang Li-Na , Li Meng-Jie , Shang Ying-Hui , Zhao Fan-Fan , Huang Han-Chang , Lao Feng-Xue
Published: August 2020

The ɛ4 allele of the Apolipoprotein E (APOE) gene in individuals infected by Herpes simplex virus type 1 (HSV-1) has been demonstrated to be a risk factor in Alzheimer’s disease (AD). APOE-ɛ4 reduces the levels of neuronal cholesterol, interferes with the transportation of cholesterol, impairs repair of synapses, decreases the clearance of neurotoxic peptide amyloid-β (Aβ), and promotes the deposition of amyloid plaque, and eventually may cause development of AD. HSV-1 enters host cells and can infect the olfactory system, trigeminal ganglia, entorhinal cortex, and hippocampus, and may cause AD-like pathological changes. The lifecycle of HSV-1 goes through a long latent phase. HSV-1 induces neurotropic cytokine expression with pro-inflammatory action and inhibits antiviral cytokine production in AD. It should be noted that interferons display antiviral activity in HSV-1-infected AD patients. Reactivated HSV-1 is associated with infectious burden in cognitive decline and AD. Finally, HSV-1 DNA has been confirmed as present in human brains and is associated with APOE ɛ4 in AD. HSV-1 and APOE ɛ4 increase the risk of AD and relate to abnormal autophagy, higher concentrations of HSV-1 DNA in AD, and formation of Aβ plaques and neurofibrillary tangles.
Estrogens Inhibit Amyloid-β-Mediated Paired Helical Filament-Like Conformation of Tau Through Antioxidant Activity and miRNA 218 Regulation in hTau Mice
Authors: Guglielmotto Michela , Manassero Giusi , Vasciaveo Valeria , Venezia Marika , Tabaton Massimo , Tamagno Elena
Published: August 2020

Background:

The risk of developing Alzheimer’s disease as well as its progression and severity are known to be different in men and women, and cognitive decline is greater in women than in men at the same stage of disease and could be correlated at least in part on estradiol levels.

Objective:

In our work we found that biological sex influences the effect of amyloid-β42 (Aβ42) monomers on pathological tau conformational change.

Methods:

In this study we used transgenic mice expressing the wild-type human tau (hTau) which were subjected to intraventricular (ICV) injections of Aβ peptides in nanomolar concentration.

Results:

We found that Aβ42 produces pathological conformational changes and hyperphosphorylation of tau protein in male or ovariectomized female mice but not in control females. The treatment of ovariectomized females with estradiol replacement protects against the pathological conformation of tau and seems to be mediated by antioxidant activity as well as the ability to modulate the expression of miRNA 218 linked to tau phosphorylation.

Conclusion:

Our study indicates that factors as age, reproductive stage, hormone levels, and the interplay with other risk factors should be considered in women, in order to identify the best appropriate therapeutic approach in prevention of cognitive impairment.
Analysis of regression prediction model of competitive sports based on SVM and artificial intelligence
Authors: Wang Jun , Qu Hongjun
Published: August 2020

The training effect is not only affected by many environmental disturbance factors, but also related to various factors such as the athlete itself. In this paper, the author analyze the regression prediction model of competitive sports based on SVM and artificial intelligence. Traditional statistical modeling simply compares existing data between players and compares them between data. Moreover, it is unable to formulate corresponding tactical strategies according to the situation of the opponent, and targeted training to strengthen the level of individual sports skills.By com-paring the effects of several kernel functions on the SVM modeling side, it is found that the RBF kernel function can make the SVM’s prediction performance the best when dealing with the speed prediction problem. The experimental results show that this parameter optimization method can significantly improve the performance of the SVM regression machine. The prediction model based on support vector machine can effectively improve the prediction direction. Using artificial intelligence and image capture technology in sports can effectively improve the statistical efficiency and prediction effect of competition.
Research on sports action recognition system based on cluster regression and improved ISA deep network
Authors: Xu Hui , Yan Rong
Published: August 2020

The movements of sports athletes are complex and difficult to identify with current smart technologies. Therefore, in order to improve the sports athlete recognition rate, this paper analyze the sports action recognition system based on cluster regression and improved ISA deep network. Through literature investigation, this paper chooses ISA neural network as the basis of the algorithm. At the same time, this paper analyzes the shortcomings of traditional ISA neural network, combines the sports player’s motion recognition requirements to improve the traditional ISA neural network, and builds a sports player motion recognition system based on the improved ISA neural network algorithm. In addition, this paper uses the network data collection method to construct the sports player action video library and takes the basketball project as an example for analysis and identifies it through feature judgment. Finally, this paper builds experiments to perform model performance analysis. The research shows that the recognition rate of basketball action is greatly improved compared with the traditional algorithm model, the results verify that the improved ISA deep network proposed in this paper has significant effectiveness in the field of human behavior recognition research.
A noval ranking approach based on incircle of triangular intuitionistic fuzzy numbers
Authors: Atalik Gultekin , Senturk Sevil
Published: August 2020

Since proposed by Zadeh in 1965, ordinary fuzzy sets help us to model uncertainty and developed many types such as type 2 fuzzy, intuitionistic fuzzy, hesitant fuzzy etc. Intuitionistic fuzzy sets include both membership and non-membership functions for their each element. Ranking of a number is to identify a relationship of scalar quantity between these numbers. Ranking of fuzzy numbers play an important role in modeling problems such as fuzzy decision making, fuzzy linear programming problems. In this study, a new ranking method for triangular intuitionistic fuzzy numbers is proposed. The method based on the incircle of the membership function and non-membership function of TIFN uses lexicographical order to rank intuitionistic fuzzy numbers. Two examples are provided to illustrate the applicability of the method. Also, a comparative study is performed to demonstrate the validity of the proposed method. The results indicate that proposed method is consistent with other methods in the literature. Also, the method overcomes the problems such as numbers being very small or close to each other.
Graph-based fuzzy approach against DDoS attacks1
Authors: Ates Çagatay , Özdel Süleyman , Anarim Emin
Published: August 2020

While internet technologies have been evolving day by day, threats against them have been increasing with the same pace. One of the most serious and commonly executed attack type is Distributed Denial of Service (DDoS) attacks. Despite there are many security mechanisms against this type of attack, there is still need for new solutions due to the occurred DDoS attacks worldwide. In this work, a DDoS attack detection approach based on fuzzy logic and entropy is proposed. Network is modelled as a graph and graph-based features are used for discriminating attack traffic from attack-free traffic. Fuzzy-c-means clustering is applied based on these features in order to show the tendencies of IP addresses or port numbers to be in a same cluster or not. Based on this uncertainty, attack and attack-free traffic are modelled. In detection phase, fuzzy membership function is used. This algorithm is tested on the real data collected from Bogaziçi University network.
Intuitionistic fuzzy c-control charts using defuzzification and likelihood methods
Authors: Ercan-Teksen Hatice , Anagün Ahmet Sermet
Published: August 2020

Control chart is one of the statistical methods to analyze the process. The use of fuzzy sets in control charts, which are divided into qualitative and quantitative data, has been applied in many studies recently. Especially for qualitative control charts, data collection is more difficult and more subjective. Therefore, fuzzy sets are used to reduce losses in data. There are many control chart studies created by type-1 fuzzy sets available in the literature. In recent years, examples of fuzzy control charts with extensions of fuzzy sets have been found. The aim of this study is to obtain c-control chart for intuitionistic fuzzy sets. For this purpose, defuzzification and likelihood methods are used. In particular, with the application of the likelihood method to intuitionistic fuzzy control charts, this will be considered as a pioneering study in the literature. In addition, a novel likelihood method was developed for intuitionistic fuzzy sets and used here to provide flexibility.
Interval-valued neutrosophic failure mode and effect analysis
Authors: Haktanır Elif , Kahraman Cengiz
Published: August 2020

Failure mode and effects analysis (FMEA) is a structured approach for discovering possible failures that may occur in the design of a product or process. Since classical FMEA is not sufficient to represent the vagueness and impreciseness in human decisions and evaluations, many extensions of ordinary fuzzy sets such as hesitant fuzzy sets, intuitionistic fuzzy sets, Pythagorean fuzzy sets, spherical fuzzy sets, and picture fuzzy sets. Classical FMEA has been handled to capture the uncertainty through these extensions. Neutrosophic sets is a different extension from the others handling the uncertainty parameters independently. A novel interval-valued neutrosophic FMEA method is developed in this study. The proposed method is presented in several steps with its application to an automotive company in order to prioritize the potential causes of failures during the design process by considering multi-experts’ evaluations.
A cognitive map integrated intuitionistic fuzzy decision-making procedure for provider selection in project management
Authors: Dursun Mehtap , Goker Nazli , Mutlu Hakan
Published: August 2020

Organizations make use of project management methodologies, which provide an effective manner to achieve managerial goals, maintain the strength of the companies in increasing competition. Efficiency in planning, budgeting, and scheduling are provided so that high quality outputs are obtained through these processes. Agile project management methodology, which has been emerged from unpredictability of customer requirements and changeable business environment, is apt to cope with the failures of traditional project management tools. Besides, lean six-sigma project management methodology has become a combination of lean and six-sigma, which were opponent methodologies previously. This paper aims to determine the most suitable outsourcing provider alternative by presenting a novel cognitive maps-based intuitionistic fuzzy decision making procedure. Interrelationships among evaluation criteria are weighted employing intuitionistic fuzzy cognitive map technique because of the causal links among evaluation criteria, vagueness, fuzziness, and hesitation in data. Moreover, the most appropriate provider alternative for both agile and lean six-sigma project management methodologies is identified by utilizing intuitionistic fuzzy TOPSIS method, which aims for minimizing the closeness to the ideal solution while maximizing the distance from the anti-ideal solution in hesitative environment. The case study is carried out in a bank that performs in Turkish banking sector.
Adaptive cognitive intelligence in analyzing employee feedback using LSTM
Authors: Dhanalakshmi R. , Sri Devi T.
Published: August 2020

Cognitive computing is the mirroring of human brain and this is made possible by using natural language processing, pattern recognition and data mining. By mirroring the human brain (Cognitive computing system), helps to solve some of the complicated problems without much of human supervision. In the fast-changing world, the major challenge every organization facing is difficulty in retaining its employees. Employees may leave an organization due to low salary, overwork, lack of opportunities and recognition, work culture, work-life imbalance etc. Better ways to retain employees is to understand their requirements and fulfill them. The proposed employee feedback sentiment analysis system collects the employee feedback reviews from open forums and perform sentiment analysis using Recurrent Neural Network – Long Short-term Memory (RNN-LSTM) algorithm. On performing Sentiment analysis, employee review comments are classified as Positive or Negative. A report is generated and sent to the HR of the organization as webapp or mobile app. The report has total number of positive and negative comments and positive and negative counts with respect to salary, work pressure etc. With the report, the organization can arrive at identifying social sentiments of their brand and may take corrective actions to retain employees which benefits both organization and employees. This paper also captures the performance of various models in training and predicting the employee feedback dataset and the models evaluated are Logistic Regression, Support Vector Machine, Random Forest Classifier, AdaBoost Classifier, Gradient Boosting Classifier, Decision Tree Classifier and Gaussian Naïve Bayes. The classification report and accuracy of each model is captured. The dataset size was gradually increased from 200 to 1000 and accuracy was predicted for each model. It was identified that the accuracy of machine learning algorithms was ranging between 66% to 85%. On training RNN-LSTM algorithm with dataset of size 30 k, the accuracy was 88%. It was identified that Deep learning algorithm RNN-LSTM performs better with huge dataset. Increasing dataset size still increase the performance of RNN-LSTM algorithm in training and prediction. Thus, the objective function of the proposed model to perform sentiment analysis on employee feedback review comments is achieved successfully.
A cognitive model for adopting ITIL framework to improve IT services in Indian IT industries
Authors: Dayal Rasbihari , Vijayakumar V. , Kushwaha Rahul Chandra , Kumar Abhishek , Ambeth Kumar V. D. , Kumar Ankit
Published: August 2020

This research paper presents a cognitive model which manages to minimize the issues of the Information Technology Infrastructure by incorporation of service management practices. The importance of this research is that this model can be replicated in other companies for the distribution of products that wish to implement improvements in their management process technological services. This work introduces the use of Information Technology Infrastructure Library or ITIL as best practice, essential methodologies for IT Management, historical evolution, methodology, service life cycle, and ITIL certifications. Service automation is widely regarded as the usefulness and improves service guarantee. One of the most useful features of automation services is that the process will run the same way every time. Such precision in the execution of repetitive executions is virtually impossible when it comes to human labor. Therefore, the automation is the best way to improve the efficiency of the service provider and the next steps of the process.
Deep learning based intelligence cognitive vision drone for automatic plant diseases identification and spraying
Authors: Latif Ghazanfar , Alghazo Jaafar , Maheswar R. , Vijayakumar V. , Butt Mohsin
Published: August 2020

The agriculture industry is of great importance in many countries and plays a considerable role in the national budget. Also, there is an increased interest in plantation and its effect on the environment. With vast areas suitable for farming, countries are always encouraging farmers through various programs to increase national farming production. However, the vast areas and large farms make it difficult for farmers and workers to continually monitor these broad areas to protect the plants from diseases and various weather conditions. A new concept dubbed Precision Farming has recently surfaced in which the latest technologies play an integral role in the farming process. In this paper, we propose a SMART Drone system equipped with high precision cameras, high computing power with proposed image processing methodologies, and connectivity for precision farming. The SMART system will automatically monitor vast farming areas with precision, identify infected plants, decide on the chemical and exact amount to spray. Besides, the system is connected to the cloud server for sending the images so that the cloud system can generate reports, including prediction on crop yield. The system is equipped with a user-friendly Human Computer Interface (HCI) for communication with the farm base. This multidrone system can process vast areas of farmland daily. The Image processing technique proposed in this paper is a modified ResNet architecture. The system is compared with deep CNN architecture and other machine learning based systems. The ResNet architecture achieves the highest average accuracy of 99.78% on a dataset consisting of 70,295 leaf images for 26 different diseases of 14 plants. The results obtained were compared with the CNN results applied in this paper and other similar techniques in previous literature. The comparisons indicate that the proposed ResNet architecture performs better compared to other similar techniques.