Miracle-dz/UniFAR-FTUs huggingface dataset:
Statistical Methods for predicting infant mortality in some selected districts of Jammu division, J&K

Introduction: Infant mortality rate (IMR) has been viewed as the vital index which can be used to measure the health level of a country or a district, and also helps to illustrate the economic development level of the country or district. Aim: The objective of this paper is to demonstrate the forecast of infant mortality rate and to develop applicable time series models for some selected districts of Jammu division, J&K, India and to find out what method can provide better performance to predict future infant deaths. Materials and Methods: We used monthly infant mortality data collected for the year 2013-2018 from four districts of Jammu division, J&K, India. We test three methods of the forecast: (1) autoregressive integrated moving average (ARIMA); (2) exponential smoothing; (3) transformation model. Result: The result showed that transformation method performed significantly better than the other methods for all the four districts, namely, Jammu, Kathua, Samba and Udhampur district of Jammu division, J&K. Future research should combine a number of different and dissimilar methods of time series to improve forecast accuracy with the ultimate aim of developing a simple and useful model for producing reasonably reliable forecasts of the infant mortality in the study area. Conclusions: The usefulness of forecasting methods in predicting the number of future infant deaths is necessary to motivate the development of a system that can reduce the future infant deaths.
Accounting for Locational, Temporal, and Physical Similarity of Residential Sales in Mass Appraisal Modeling: The Development and Application of Geographically, Temporally, and Characteristically Weighted Regression

Geographically weighted regression (GWR) has been recognized in the assessment community as a viable automated valuation model (AVM) to help overcome, at least in part, modeling hurdles associated with location, such as spatial heterogeneity and spatial autocorrelation of error terms. Although previous researchers have adjusted the GWR weights matrix to also weight by time of sale or by structural similarity of properties in AVMs, the research described in this paper is the first that has done so by all three dimensions (i.e., location, structural similarity, and time of sale) simultaneously. Using 24 years of single-family residential sales in Fairfax, Virginia, we created a new locally weighted regression (LWR) AVM called geographically, temporally, and characteristically weighted regression (GTCWR) and compared it with GWR-based models with fewer weighting dimensions. GTCWR was the only model to achieve IAAO-accepted levels of the coefficient of dispersion (COD), price-related differential (PRD), price-related bias (PRB), and median assessment-to-sale price ratio in both the training and testing samples, although it did not fully correct the existence of heteroscedasticity. With lower PRD and PRB levels, the application of temporal weighting to this data set did appear to help reduce indicators of vertical inequity. Along with an equitable, uniform, and defensible methodology that mirrors the sales Accounting for Locational, Temporal, and Physical Similarity of Residential Sales in Mass Appraisal Modeling: The Development and Application of Geographically, Temporally, and Characteristically Weighted Regression BY PAUL E. BIDANSET; MICHAEL MCCORD, PH.D.; JOHN R. LOMBARD, PH.D.; PEADAR DAVIS, PH.D., MRICS; and WILLIAM J. MCCLUSKEY, PH.D.
Synthesis of fused Azo-linked 1, 2, 4-Triazole-3-Thione derivatives using Ag2S/RHA-MCM-41 nanocomposite

* Corresponding Author Email: nikpassand@iaurasht.ac. ir How to cite this article Jafarian Z. , Nikpassand M. , Pourahmad A. , Zare Fekri L. Synthesis of fused Azo-linked 1, 2, 4-Triazole-3-Thione derivatives using Ag2S/RHA-MCM-41 nanocomposite. Int. J. Nano Dimens. , 2022; 13(1): 117-125. Abstract Magnetic nanoparticles have received much attention in synthesizing organic compounds due to their unique properties such as high contact surface, recyclability, and easy separation. In this study, Rice husk ash (RHA), an agriculture waste, was used as a silica source for MCM-41 synthesis. Ag2S/RHA-MCM-41 nanocomposite synthesized and characterized with FT-IR, SEM, and XRD. Prepared nanocomposite used for the synthesis of azo-linked 1, 2, 4-triazole-3-thione derivatives. Our study result showed that Ag2S/RHA-MCM-41 nanocomposite showed high activity in the synthesis of azo-linked 1, 2, 4-triazole-3-thione derivatives because of good yields and desirable reaction time. The structure of all compounds was determined by FTIR, 1H-NMR and 13C-NMR spectroscopy. In all reactions, the catalyst is easily removable and reusable, and its catalytic activity is maintained after five runs.
Corporate Social Responsibility and Consumer-Company Identification in Vietnamese Project-Based Organizations

In the past four decades, corporate social responsibility (CSR) issues have grown substantially due to the increasing demand for transparency and growing expectations that corporations should manage and improve their social, environmental, and economic performance. As a result, most organizations, companies, and governments provide CSR reports, while a large number of companies are still engaged in defining and integrating CSR into several aspects of their business. CSR is an obligation to society (Lee, 2020). The linkage between CSR and consumer-company identification (CCI) is important under company stakeholders. Consumers who care about those issues often change their shopping habits to bring greater value to the community. They will avoid buying environmentally or socially harmful products, and actively seek the products and services of the companies that carry out social responsibility. Companies conducting CSR activities such as charity works or environmental activities will be easy to associate as a responsible organization for always meeting the necessity of society. Therefore, companies must consider CSR a long-term strategy. The strategic approach to CSR plays an increasingly significant part in the business competitiveness which helps create companies’ values while gains trust and respect from the consumers, partners in particular, and the social community in general. This study is conducted to show evidence from project-based organizations about the CSR factors that influence consumer loyalty and the impact level of those factors on customer loyalty.
Autonomous decentralized structural health monitoring using smart sensors

Though smart sensor technology has seen substantial advances during recent years, implementation of smart sensors on full‐scale structures has been limited. Direct replacement of wired sensing systems with wireless sensor networks is not straightforward as off‐the‐shelf wireless systems are unlikely to provide the data users expect. The difficulty arises, in part, because centralized systems common for wired measurements are not scalable to large numbers of smart sensors. Decentralized computing is required to harvest the rich information that a dense array of smart sensors can make available for structural health monitoring (SHM). Decentralized system can be effectively managed by each sensor node and cluster autonomously performing tasks such as sensing and damage detection. Taking advantage of recent developments in middleware services which provide basic functionality for structural vibration measurements (e.g. synchronized sensing and reliable communication) this paper proposes an autonomous decentralized SHM approach using smart sensors. A set of algorithms that mesh well with the decentralized approach are first proposed and implemented on smart sensors. Finally, experimental validation of the implemented system is given and its damage detection capability is discussed. Copyright © 2009 John Wiley & Sons, Ltd.
Sustainable Development and Livelihoods of Rohingya Refugees in Bangladesh: The Effects of COVID-19

Received: 5 August 2021 Accepted: 30 September 2021 Bangladesh is one of the top refugee-hosting countries of the world and adversely affected by the COVID-19. This paper aims to identify how the COVID-19 pandemic affects the Rohingya refugee and expose the vulnerability that challenges SDGs. The study follows a system approach grounded on a sustainable development model and uses secondary sources of data. The study found that fragmented and random policies in refugee crisis management during the COVID-19 reveals the policy lacks structural fragility due to inadequate policy and programs. Besides, the limited number of health care, food, education, washing facilities, housing, and the utilization of inferior materials in camps put pressure on the refugee health, education, and well-being during COVID-19. It also reduces the monetary funds, which affects humanitarian support, and limits the aid to SDGs in refugee camps due to restrictive policies. Moreover, refugees' inability to include an inclusive social security system is far from existing social inequality. This paper calls for robust policies and programs with adequate funding for structural logistics and effective service delivery in refugee management for their future wellbeing and promoting SDGs in refugee camps.
Mammogram Classification and Segmentation Through Deep Learning

Given the extreme importance in early detection of breast cancer, a compelling search for Computer-Aided Detection (CAD) techniques drove Deep Learning (DL) researchers to investigate potential mammography screening applications. This work proposes the use of sophisticated Convolutional Neural Networks (CNNs) for classification and segmentation of mass and Micro-Calcification (MC) lesions on the publicly available INbreast dataset. Using an Attention Dense U-Net model, lesion segmentations are extracted with a Dice Coefficient of (0.71 ± 0.08) for masses and (0.58 ± 0.05) for MCs. As a result, classification using a Dense Multi-View model incorporating these predicted lesion segmentations shows competitive results regarding the State of the Art in fully-automated classification of breast screening exams (Normal, Benign, Malignant), achieving a 3-Class Mean AUC of (0.79 ± 0.06).
Ozone Profile Retrieval

The TOPAS :::::::: (Tikhonov :::::::::: regularized ::::: Ozone :::::: Profile :::::::: retrievAl :::: with ::::::::::: SCIATRAN) algorithm to retrieve vertical profiles of ozone from space-borne observations in nadir viewing geometry has been developed at the Institute of Environmental Physics (IUP) of the University of Bremen and applied to TROPOMI ::: the ::::::::::: Tropospheric :::::::::: Monitoring ::::::::: Instrument ::::::::::: (TROPOMI) L1B spectral data version : 2. The spectral data between 270 and 329 nm are used for the retrieval. A re-calibration of the measured radiances is done using ozone profiles from MLS/Aura. Studies with synthetic spectra show that individual profiles 5 in the stratosphere can be retrieved with the accuracy :: an ::::::::: uncertainty : of about 10%. In the troposphere, the retrieval errors are larger depending on the a-priori profile used. The vertical resolution above 18 km is about 6 – 10 km and it degrades to 15 – 25 km below. The vertical resolution in the troposphere is strongly dependent on the solar zenith angle (SZA). The ozone profiles retrieved from TROPOMI with the TOPAS algorithm were validated using data from ozone sondes :::::::::: ozonesondes and stratospheric ozone lidars. Above 18 km, the comparison with sondes shows excellent agreement within less than ± 5% 10 for all latitudes. The standard deviation of mean differences is about 10%. Below 18 km, the relative mean deviation in the tropics and northern latitudes is still quite good remaining within ± 20%. At southern latitudes larger differences of up to +40% occur between 10 and 15 km. The standard deviation is about 50% between 7-18 km and about 25% below 7 km. The validation of stratospheric ozone profiles with ground-based lidar measurements also shows very good agreement. The relative mean deviation is below ± 5% between 18 – 45 km with a standard deviation of 10%. TOPAS retrieval results for one day of 15 TROPOMI observations were compared to MLS and :::: ozone ::::::: profiles ::::: from ::: the ::::::::: Microwave ::::: Limb ::::::: Sounder :::::: (MLS) ::: on ::: the ::::: Aura :::::: satellite :::: and ::: the ::::: Ozone :::::::: Mapping :::: and :::::: Profiler ::::: Suite ::::: Limb :::::: Profiler : (OMPS-LPdata : ). The relative mean difference was found to be largely below ±5% between 20 – 50 km with exception of ::::: except :: at very high latitudes.
Classification using a word embedding techniques

Word embedding is one of the most commonly used techniques for finding word similarity or identifying test context. In this paper, I am illustrating the classification process with the help of word vectors obtained from word embedding techniques to come up with interesting classified results. Here, the process of word embedding to generate word vectors for every role followed by the clustering algorithms implementation is required. Thus, this paper focuses on various word embedding algorithms and clustering approaches that can go hand in hand to be used in applications like subtopic detection, single document summarization, etc.
Sensitivity of EnlistTM and Roundup Ready Xtend® Technologies to Auxin Herbicides and Comparison of Resistance to Susceptible Cotton and Soybean Cultivars

Increases in weed resistance have led to the development of new herbicide-resistant crop technologies, namely the Roundup Ready Xtend and Enlist weed control systems. These new technologies provide resistance to applications of the synthetic auxins dicamba or 2,4-D, respectively, in traited cotton or soybean. It is unknown if there is any resistance to other herbicides within the synthetic auxin group (WSSA Group 4) in these traited crops. Experiments were conducted with auxin herbicides representing all five families within WSSA Group 4. Herbicides were applied either preemergence (PRE) or postemergence (POST) relative to the crop in a single application. Applications were made at a labeled rate (1X) and 1/16 of the labeled rate to LibertyLink, Xtend, and Enlist soybean and cotton cultivars to test for crossresistance of the herbicides with any of these new technologies. Another study was conducted to determine response (growth and yield) of Roundup Ready and Roundup Ready 2 Xtend soybean to reduced rates of dicamba [28 g ae ha (1/20x), 7 g ae ha (1/80x), and 3.5 g ae ha (1/160x)] compared with florpyrauxifen-benzyl at rates of 1.46 g ae ha (1/20x), 0.36 g ae ha (1/80x), and 0.18 g ae ha (1/160x). The cross-resistance trial revealed an increased resistance by Enlist soybean and cotton, not only to 2,4-D, but also triclopyr and fluroxypyr applied PRE or POST. The Roundup Ready Xtend crop system was found to possess commercial resistance only to dicamba at either application timing. From this research, it was concluded that resistance of herbicide-resistant crops to a particular herbicide within the WSSA synthetic auxin Group 4 herbicides does not necessarily confer resistance to all herbicides within that group. The drift trial, where low rates of dicamba and florpyrauxifen-benzyl were evaluated following application at the R1 growth stage, indicated that the Roundup Ready 2 Xtend soybean were resistant to low rates of dicamba, which was expected, but not to low rates of florpyrauxifen-benzyl. The Roundup Ready cultivar was injured by all rates of dicamba and florpyrauxifen-benzyl, with increasing injury as rate of application increased. Yield, the second parameter compared, could not be predicted accurately by visible assessments of injury. Table of
Method of numerical simulation flow on rough Cartesian calculation grids

The use of an unstructured computational grid in computational aerohydrodynamics is associated with a number of difficulties: the non-conservativeness of the momentum balance equation, the manifestation of nonphysical grid effects, a decrease in the time step for the Courant-Friedrichs-Levy condition, and the complexity of modeling a dynamic grid. Of course, these difficulties are solvable, however, they require complex logic of mathematical algorithms, which leads to an increase in the requirements for the resource of the software product. Therefore, the author cultivates a low-resource method for calculating currents on coarse calculated Cartesian grids. This method has the same logic for the entire computational domain, but it requires solving the problem of flow turning in places with complex geometry. To calculate flows on rough Cartesian computational grids, the method of isentropic rotation of the flow in cells adjacent to the surface is proposed. The structure of the computational domain with masks of the guiding properties and the adjacent layer is described. The algorithm of isentropic rotation of the flow using the method of features is given. An algorithm is described for the effect of the wall on the intensity of the features involved in the rotation of the flow.
Increased risk of psychiatric sequelae of COVID-19 is highest early in the clinical course

Background: COVID-19 has been shown to increase the risk of adverse mental health consequences. A recent electronic health record (EHR)-based observational study showed an almost two-fold increased risk of new-onset mental illness in the first 90 days following a diagnosis of acute COVID-19. Methods: We used the National COVID Cohort Collaborative, a harmonized EHR repository with 2,965,506 COVID-19 positive patients, and compared cohorts of COVID-19 patients with comparable controls. Patients were propensity score-matched to control for confounding factors. We estimated the hazard ratio (COVID-19:control) for new-onset of mental illness for the first year following diagnosis. We additionally estimated the change in risk for new-onset mental illness between the periods of 21-120 and 121-365 days following infection. Findings: We find a significant increase in incidence of new-onset mental disorders in the period of 21-120 days following COVID-19 (3.8%, 3.6-4.0) compared to patients with respiratory tract infections (3%, 2.8-3.2). We further show that the risk for new-onset mental illness decreases over the first year following COVID-19 diagnosis compared to other respiratory tract infections and demonstrate a reduced (non-significant) hazard ratio over the period of 121-365 days following diagnosis. Similar findings are seen for new-onset anxiety disorders but not for mood disorders. Interpretation: Patients who have recovered from COVID-19 are at an increased risk for developing new-onset mental illness, especially anxiety disorders. This risk is most prominent in the first 120 days following infection.
Relative Localization Method of Wet Spot of Grain using Array of Passive RFID Tags

Radio Frequency Identification (RFID) enables a large number of object monitoring since semi/passive tags are independent of batteries. In our previous work, the possibility of using different wireless technologies such as Wireless Sensor Network (WSN), Wireless Local Area Network (WLAN) and Radio Frequency Identification (RFID) to determine the moisture content in rice was investigated. Finding from our previous work suggest that RFID can be used to determine the moisture content of rice. While numerous research have been conducted for moisture content of grain, however, to author’s knowledge, there is only a few studies conducted on the localization of grain hostpot. Therefore, this study aims to investigate if the passive RFID array can be used to localize the location of the wet spot of grain. Prior, the experiment, a suitable setting for the RFID system were determined. In addition, a simple test was conducted to select a suitable operating frequency. From the investigation, the result indicates that only frequency channels 865, 866, 867, 868 and 869 MHz can detect all 30 tags. Meanwhile, frequency channel in the range 902 to 928 MHz detects 26 to 29 unique tags. Hence, 868 MHz was selected as the operating frequency throughout the experiment. The findings indicate that the RSSI value measured by the RFID reader decreased as the moisture of the sample increased when the tags were blocked by the sample placed at the designated location during the test.
Design of a Mechatronic Interface with Compliant Manipulator for Robot Assisted Echocardiography

A compliant manipulator with a compound soft actuator is proposed for robot-assisted echocardiography. The target application is devoted to the TOE echo (Trans-oesophageal echocardiography), which is conventionally performed by medical practitioners. The manual manipulation of the echocardiography probe shows significant risks such as human errors, exposure to ionizing radiation, and multitasking complexity. Automation of TOE provides advantages in terms of control, safety, and workload of the operator. This paper proposes a teleoperated robotic system assisting the physician to perform TOE, to be used in cardiac catheterization laboratories as well as hybrid operation theatres. A system containing a holder with master-slave Dynamixel servos and a manipulator with soft actuators has been developed. To alleviate the major lack of the previous designs in conducting the insertion tube, a robotic arm with a soft structure is proposed that has not hazards of conventional robot manipulators. The fundamental equations and relations for quasi-static control of the system are developed in this paper.
Biodeterioration of historic timber structures: A comparative analysis

Abstract Service life of timber structures in the north of Europe is decreased mainly by biological agents. Increasing risk of biological infestation due to global warming is widely discussed nowadays. Historic timber structures which have been monitored for decades provide us with valuable information on this subject. An investigation of the structures in the Kizhi museum, located in the northwest of Russia was carried out in the 1970s and in 2011–2012. Identification of wood-decay fungi that destroy constructive elements of seventeenth- and nineteenth-century monuments showed that the most frequent damages are caused by brown rot fungi. At the same time, imperfect fungi and ascomycetes which cause soft rot began to play a significant role in damaging historic timber structures. Borers (Hadrobregmus pertinax L. and H. confusus Kraaz) play the leading part in reducing the service life of seventeenth- and nineteenth-century heritage objects. During a forest inventory, some wood-borers not registered previously as timber structure pests in the Kizhi archipelago region (Republic of Karelia, Russia) were found. Twenty-seven species of foliose and fruticose lichens and ten species of crustose lichens were found on the monuments' structural elements.