bluuebunny/crossref_metadata_2025 huggingface dataset:
Semantics based English-Arabic machine translation evaluation
Authors: Beseiso Majdi , Tripathi Samiksha , Al-Shboul Bashar , Aljadid Renad
Published: June 2022

Some classic machine translation (MT) Evaluation methods, such as the bilingual evaluation understudy score (BLEU), have notably underperformed in evaluating machine translations for morphologically rich languages like Arabic. However, the recent remarkable advancements in the domain of word vectors and sentence vectors have opened up new research avenues for low-resource languages. This paper proposes a novel linguistic-based evaluation method for English-translated sentences in Arabic. The proposed approach includes penalties based on length, positions, and context-based schemes such as part-of-speech tagging (POS) and multilingual sentenceBERT (SBERT) models for machine translation evaluation. The proposed technique is tested using pearson correlation as a performance evaluation parameter and compared with state-of-the-art techniques. The experimental results demonstrate that the proposed model evidently outperforms other MT evaluation methods such as BLEU.
Image anomalies detection using transfer learning of ResNet-50 convolutional neural network
Authors: Omer Zaid Taher , Abbas Amel Hussein
Published: June 2022

With the quick advancement of keen fabricating, information-based blame determination has pulled in expanding attention. As one of the foremost prevalent strategies of diagnosing errors, deep learning has accomplished exceptional comes about. Be that as it may, due to the truth that the estimate of the seeded tests is little in diagnosing mistakes, the profundities of the deep learning (DL) models for fault conclusion are shallow compared to the convolutional neural network in other regions (including ImageNet), which limits the accuracy of the final prediction. In this paper, ResNet-50 with a 25 convolutional layer depth has been proposed to diagnose anomalous images. Trained ResNet-50 applies ImageNet as a feature extractor to diagnose errors. It was proposed on three sets of data which are the bottle, the spoon, and the carton, and the proposed method was achieved. The prediction accuracy of the data set was 99%, 95% and 90%, respectively.
News classification using light gradient boosted machine algorithm
Authors: Rahmatul Kholiq Muhammad Hatta , Wiranto Wiranto , Widya Sihwi Sari
Published: June 2022

News classification is a complex issue as people are easily convinced of misleading information and lack control over the spread of fake news. However, we ca n break the problem of spreading fake news with artificial intelligence (AI), which has developed rapidly. This study proposes a news classification model using a light gradient boosted machine (LightGBM) algorithm. The model is analyzed using two feature extraction techniques, count vectorizer and Tfidf vectorize r and compared with a deep learning model using long - short term memory (LSTM). The experimental evaluation showed that all LightGBM models outperform LSTM. The best model is the count vectorizer Li ghtGBM, which achieves an accuracy value of 0.9933 and an area under curve (AUC) score of 0.9999.
Performance evaluation of unmanned aerial vehicle communication by increasing antennas of cellular base stations
Authors: Kapoor Rajesh , Shukla Aasheesh , Goyal Vishal
Published: June 2022

The utilization of unmanned aerial vehicles (UAVs) increases with increased performance of their communication link with the ground remote station. Integrating UAVs with existing cellular networks provides the possibility of enhanced performance of communication links. The base stations of existing cellular networks are installed with fixed number of antennas. The performance of UAV communication links can be further enhanced by increasing antennas of cellular base stations of existing networks using multiple antenna techniques such as multi ple input multiple output (MIMO). In this proposed scheme, Massive MIMO technology is used for UAV communications, wherein hundreds of antennas are mounted on cellular base stations. This set up provides significant advantage in terms of enhancement in per formance of UAV communication links, as compared to existing methods of UAV communication. In this paper, performance evaluation of UAV communication links is carried out by increasing the number of antennas at base stations of existing cellular networks. For this evaluation, firstly basic multiple antennas techniques such as point - to - point MIMO and multi - user MIMO (MU - MIMO) are covered based on existing studies and findings. Subsequently, an antenna dependent closed form expression for uplink channel capac ity of massive MIMO based UAV communication links is derived, with few numerical results.
A novel energy efficient routing scheme for wireless sensor networks
Authors: Hiremath Veeresh , Bidkar Gopal
Published: June 2022

In the current rapid developing and smart world, the wireless sensor networks domain is among the most emergent fields with plenty of applications such as healthcare, wildlife, environmental monitoring, defense, and landslide detection. Distribution of cluster heads along with the selection of cluster heads is essentially vital for optimizing various network performance parameters. In this paper, a novel energy efficient routing scheme based on probabilistic sector wise clustering has been proposed, which results in energy saving in conjunction with superior network lifetime for wireless sensor networks. In the proposed routing technique, the sensing field is divided into multiple sectors and clusters in five different types. Nodes in the sector can communicate directly with the base station in one-hop or through the gateway node in two-hops. Nodes in the cluster communicate to the base station through the cluster head in three-hops. The simulation results of all five types are compared in terms of their life span. Life span of the network is analyzed by considering the round number in which the first node dies, the round number till which 80% of the nodes are alive, 50% of nodes are alive and 20% of the nodes are alive.
Outlier tolerant adaptive sampling rate approach for wireless sensor node
Authors: Selvaraj Sunil Kumar , Pundikai Venkatramana Bhat
Published: June 2022

Nowadays the wireless sensor network (WSN) has been used for variety of applications and still lot of research in progress around the corner for the betterment of the wireless sensor network technology. In this paper, one such issues related to energy consumption in sensor node due to fixed sampling interval of sensing unit and its impact on redundant data is discussed with a possible solution. The association of sampling interval and its impact on energy dissipation in sensor node enforces the need for study on energy efficient adaptive sampling interval approach. The lack of serious consideration of outlier in sensor data degrades the performance of the existing adaptive sampling interval approach. The result of the proposed approach of in-network clustering algorithm shows the better efficiency towards detecting the outlier in real time. The results also showcase the better efficiency of proposed approach in terms of rapid optimization of sampling interval compared to simple variance based approach.
Spectral efficiency and performance improvement of coherent optical transmission system
Authors: Kadhim Muthanna Ali , Fattah Ali Yousif , Sabri Atheer Alaa
Published: June 2022

This paper presents an orthogonal frequency division multiplexing (OFDM) for a long-haul optical transmission system with high-rate transferability to alleviate dispersion effects. In addition, we suggest combining polarization division multiplexing (PDM) with coherent OFDM (CO-OFDM) to increase spectral efficiency (SE). Based on OptiSystem (2021) version 18.0" software package, a 100 Gbps single-channel PDM-CO-OFDM transmission system is investigated using different modulation formats; bipolar phase keying (BPSK), quadrature phase shift keying (QPSK), Eight-Phase-Shift Keying modulators (8-PSK), and quadrature amplitude modulation (16-QAM). A 60 km span of standard single-mode fiber (SSMF) cable is employed in this investigation. The system's performance and spectral efficiency have been evaluated by comparing against the different modulation schemes. The outcomes that were got show that the BPSK modulation scheme has the longest transmission distance and requires a lesser level of optical signal to noise ratio (OSNR) at the receiver side. Concerning spectral efficiency, 16-QAM outperforms the others. Farther, the impact of employing ultra-low loss and large effective area fiber in reducing loss and nonlinear effects in the optical channel for 16-QAM modulation formats is examined. The result found that the system with advanced fiber has superior performance than the SSMF. The bit error rate (BER) of 0.033 (20% concatenated forward error correction (FEC) threshold) is used as a baseline.
Analysis study of quality factor and bit error rate at wavelength change
Authors: Mahmood Fadhela Thaeer , Ali Alaa H. , Ali Haeder Alaa H.
Published: June 2022

Gigabit - per - second data speeds can be achieved via free space optics (FSO) lines, which needless system complexity. On the other hand, the link's availability across a wide range of atmospheric circumstances is a major worry. As a result of the increased signal attenuation caused by the linkages being weather - dependent, their efficiency decreases. Up to 70 dB/km of attenuation can be caused by bad weather on a 500 - meter free space optics link. In this work, transmission windows of 1310 nm, 850 nm , and 1550 nm are analyzed and compared using the free space optics link. by using the Simulation program o pti system such as the q uality factor, the minimal bit error rate (BER), and the e ye diagram is taken into account. Analyzer findings are compared to establish the optimal wavelength for a transmitter under poor weather conditions.
The design of viscometer with smartphone controlling
Authors: E. Suleimenov Ibragim , A. Mun Grigoriy , B. Kabdushev Sherniyaz , Alikulov Adilet , B. Shaltykova Dina , Moldakhan Inabat
Published: June 2022

New design of a viscometer based on the s tokes viscosity measurement method is proposed. The principle of operation of this viscosimetr is based on the use of ball periodic alternated movement in a horizontally positioned cuvette that filled with the test liquid. The movement appears under the in fluence of a magnetic field that created by two electromagnets. Registration of the ball movement inside the cuvette is carried out using an optoelectronic pair. A distinctive feature of the proposed design is control by using a program that installed on t he user's smartphone, which also carries out the primary data processing. Data transmission is carried out over the radio channel using a Bluetooth module. Disposable cuvettes are used for measurements. This approach makes it possible to significantly redu ce both the device production costs and operating costs by eliminating most of the operations for the device preparing for working (the vast majority of existing types of viscometers require thorough flushing of all units in contact with the test medium). In addition, the proposed approach excludes the occurrence of measurement errors associated with insufficiently thorough preparation of the device for operation.
IoT-based communal garbage monitoring system for smart cities
Authors: Azyze Nur Latif Azyze Mohd Shaari , Isa Ida Syafiza Md , Chin Thomas See
Published: June 2022

In Malaysia, approximately 38,000 metric tons of garbage are generated due to human daily activities. This is due to the growing population in the urban area, hence increasing the tendency of overflowing garbage due to the insufficient space in the garbage container. In addition, the tight schedule of the garbage collection allows the spreading of the toxic odor as the garbage start to rotten up, hence leading to air pollution. Therefore, a systematic waste management system is important to provide a healthy and clean environment to the community. In this work, a communal garbage monitoring system has been developed to notify the administrator of the status of the container. Besides monitoring the level of garbage, the system is also designed to monitor the temperature, humidity, and air quality of the garbage container. These monitored data will be uploaded at the cloud for real-time monitoring. Compared to the other work, a real test-bed implementation has been conducted considering different types of waste including food waste, paper, bottles and metal; to determine the accuracy of the developed system. The results show that the system has high reliability and high accuracy with 96% for food waste and 98% for other types of waste.
An enhanced hybridized approach for group recommendation via reliable ratings
Authors: Behl Rachna , Kashyap Indu
Published: June 2022

A group recommender system aim's to provide relevant information to all members of the group. To determine group preferences, the majority of existing studies use aggregation approaches. An aggregation method is a strategy for recommending products to a group by combining the individual preferences of group members. So far, a slew of different types of aggregation algorithms has been discovered. However, they only aggregate one component of the offered ratings (e.g., counts, rankings, high averages), which limits their ability to capture group members' proclivities. This study proposes a novel aggregation method called weighted count that aggregates ratings by providing weights equal to the number of users who provide ratings to an item (location). In addition, the study proposes combining additive utilitarian and weighted count approaches to highlight popular locations on which group members agreed. Experiments on a benchmark check-in dataset demonstrated that the proposed blended technique surpasses the existing methods significantly.
High performance time series models using auto autoregressive integrated moving average
Authors: Al-Qazzaz Redha Ali , Yousif Suhad A.
Published: June 2022

Forecasting techniques have received considerable interest from both researchers and academics because of the unique characteristics of businesses and their influence on several areas of the economy. Most academics utilize the autoregressive integrated mov ing average (ARIMA) approach to forecasting the future. However, researchers face challenges, such as analyzing the data and selecting the appropriate ARIMA parameters, especially with large datasets. This study investigates the use of the automatic ARIMA (Auto ARIMA) function for forecasting Brent oil prices. It demonstrates the benefits of using Auto ARIMA over ARIMA for determining the appropriate ARIMA parameters based on measures such as root mean square error ( RMSE ) , mean absolute error ( MAE ) , and aka ike information criterion ( AIC ) without requiring the attention of an expert data scientist as it bypasses several steps needed for manual ARIMA. Auto ARIMA produced an RMSE of 12.5539 and an AIC of 1877.224, which are comparable to the values resulting fr om the manual ARIMA with the help of expert data scientists; thus, it saves analysis time and offers the best model result.
Chat network study and design using HTML and PHP web programming
Authors: Hussein ‬‏ ‪Angham Khalid
Published: June 2022

Chat rooms becoming a part of human life, from sharing and exchanging information such as texts, pictures and messages. Many begin to share the latest news and images related to news in the media field as well as chat messaging in the Internet and targeting customers in business, jokes, music and video in the entertainment field. In this paper a chat web site are designed using Hyper Text Markup language (HTML) and Personal Home Page (PHP) web programming languages with security and authentication features added to it to keep user privacy and personal information unattached, and Apache http server are used to test it.
Blockchain associated machine learning and IoT based hypoglycemia detection system with auto-injection feature
Authors: Mahzabin Rahnuma , Sifat Fahim Hossain , Anjum Sadia , Nayan Al-Akhir , Kibria Muhammad Golam
Published: June 2022

Hypoglycemia is an unpleasant phenomenon caused by low blood glucose. The disease can lead a person to death or a high level of body damage.
 To avoid significant damage, patients need sugar. The research aims at implementing an automatic system to detect hypoglycemia and perform automatic sugar injections to save a life. Receiving the benefits of the internet of things (IoT), the sensor’s data was transferred using the hypertext transfer protocol (HTTP) protocol. To ensure the safety of health-related data, blockchain technology was utilized. The glucose sensor and smartwatch data were processed via Fog and sent to the cloud. A Random Forest algorithm was proposed and utilized to decide hypoglycemic events. When the hypoglycemic event was detected, the system sent a notification to the mobile application and auto-injection device to push the condensed sugar into the victim’s body. XGBoost, k-nearest neighbors (KNN), support vector machine (SVM), and decision tree were implemented to compare the proposed model's performance. The random forest performed 0.942 testing accuracy, better than other models in detecting hypoglycemic events. The system’s performance was measured in several conditions, and satisfactory results were achieved. The system can benefit hypoglycemia patients to survive this disease.
Cost-effective resource and task scheduling in fog nodes
Authors: Shamman Ali Hussein , Alasadi Hussein Ali , Ameen Hussein Ali , Rasol Zaid Ibrahim , Gheni Hassan Muwafaq
Published: June 2022

Cloud services are the cutting edge technology, however the growing demand for the internet of things has certain limitations which are high latency expectation and high cost of cloud resources, and this is caused by long-distance between application and cloud. Fog computing is a distributed extension of the cloud, which provide storage and computation at the network level. It consists of an internet of things (IoT) application, a fog control node, and a fog access node. This research works towards minimizing the cloud cost in scheduling. For this purpose, a cost-effective task and user scheduling algorithm are performed. The first task scheduling model is composed based on composers' roles after that task scheduling algorithm is performed to handle the various task at the fog access node in an optimized manner. Finally, the reallocation mechanism reduces the time and service delay. For the analysis purpose extensive simulation is carried out and performance statistics were compared with other existing algorithms. It was observed that the proposed algorithm provides highly cost-optimized user and task scheduling with better performance statistics and reduces the delay in the task by providing optimization in the concurrent task at the fog node.
Prediction of student satisfaction on mobile-learning by using fast learning network
Authors: Sultan Laman Radi , Abdulateef Salwa Khalid , Shtyat Bushra Abdullah
Published: June 2022

The rapid advancement of mobile technologies over the past decade has had a significant impact on the appearance of M-learning applications. The research proposes the fast learning network model to investigate and identify the factors that affect student satisfaction in M-learning for the University of Tikrit students. The research model is conducted utilizing a questionnaire of 300 participating students based on variables. This research showed that the proposed model's perfor mance was superior to artificial neural network,
 k-nearest neighbors, and multilayer perceptron algorithms. The accuracy and specificity of predicting the student satisfaction coefficients in M-learning were 91.6% and 92.85%, respectively. The proposed findings demonstrate that diversity in the evaluation, teacher attitude and response, and quality of technology are key operators of student satisfaction.
Improving SpellChecking: an effective Ad-Hoc probabilistic lexical measure for general typos
Authors: Gueddah Hicham , Nejja Mohamed , Iazzi Said , Yousfi Abdellah , Aouragh Si Lhoussain
Published: June 2022

Since the era of learning to write by human beings,  mistakes made in typing words have occupied a privileged place in linguistic studies, integrating new disciplines into school curricula such as spelling and dictation. According to exhaustive studies that we have done in the field of spellchecking errors made in typing Arabic texts, very few research works that deal with typographical errors specifically caused by the insertion or missing of the blank-space in words. On the other hand, spelling correction software remains ineffective for handling this type of errors. Failure to process errors due to the insertion/missing of blankspace between and in words leads and brings us back to situations of ambiguity and incomprehension of the meaning of the typed text. To remedy this limitation of correction, we propose in this article an ad-hoc probabilistic method which is based jointly on two approaches. The first approach treats the errors due to deletion or missing of blank-space between or inside words, while the second puts emphasis in correcting space insertion errors in a word of course in addition to other kinds of elementary editing errors (addition, deletion, permutation of characters). Our new approach combines edit distance with n-gram language models to correct the errors already mentioned. Our new approach gave an accuracy rate that reaches 98,14% for missing blank-space errors (noted MBSE) and 89,5% for insertion blank-dpace errors (noted IBSE), which gives an average correction rate of around 95,26%. These results are very encouraging and show the interest and the importance of our approach.
Modeling and simulation of electro-hydraulic telescopic elevator system controlled by programmable logic controller
Authors: Al-Had Istabraq Hassan Abed , Mohammed Farag Mahel , Mohammed Jamal A.-K.
Published: June 2022

Traditional hydraulic cylinders are widely used in industry as load lifting tools. There is difficulty in employing these cylinders in narrow installation space like building elevators as well as they require a long working stroke, so solving this problem requires using the telescopic hydraulic cylinder instead. This cylinder is a unique hydraulic cylinder design that uses a sequence of decreasing diameters to create a long operating stroke in a compact-retracted form. In this work, the Auto Station software is used to build a telescopic hydraulic cylinder model that includes hydraulic elements such as double-acting hydraulic telescopic cylinders, pump, valves, pipeline, and filter, as well as electrical parts such as programmable logic controller (PLC), push-bottoms, and position sensors. The proposed model is operated by a PLC controller and has three floors with an overall height of around 300 cm for lifting a 100 kg payload. The accuracy and validity of this model in lifting big weights were demonstrated by the analytical findings of characteristic curves for cylinder position and velocity. This model can be used a basic reference to analyze and construct hydraulic cylinders with any number of stages. The findings of simulations reveal that a quick change in pressure due to phase change causes multi-phase vibration.
Health State Utility Values in People With Stroke: A Systematic Review and Meta‐Analysis
Authors: Joundi Raed A. , Adekanye Joel , Leung Alexander A. , Ronksley Paul , Smith Eric E. , Rebchuk Alexander D. , Field Thalia S. , Hill Michael D. , Wilton Stephen B. , Bresee Lauren C.
Published: June 2022

Background

Health state utility values are commonly used to provide summary measures of health‐related quality of life in studies of stroke. Contemporaneous summaries are needed as a benchmark to contextualize future observational studies and inform the effectiveness of interventions aimed at improving post‐stroke quality of life.

Methods and Results

We conducted a systematic search of the literature using Medline, EMBASE, and Web of Science from January 1995 until October 2020 using search terms for stroke, health‐related quality of life, and indirect health utility metrics. We calculated pooled estimates of health utility values for EQ‐5D‐3L, EQ‐5D‐5L, AQoL, HUI2, HUI3, 15D, and SF‐6D using random effects models. For the EQ‐5D‐3L we conducted stratified meta‐analyses and meta‐regression by key subgroups. We screened 14 251 abstracts and 111 studies met our inclusion criteria (sample size range 11 to 12 447). EQ‐5D‐3L was reported in 78% of studies (study n=87; patient n=56 976). The pooled estimate for EQ‐5D‐3L at ≥3 months following stroke was 0.65 (95% CI, 0.63–0.67), which was ≈20% below population norms. There was high heterogeneity (I
2
>90%) between studies, and estimates differed by study size, case definition of stroke, and country of study. Women, older individuals, those with hemorrhagic stroke, and patients prior to discharge had lower pooled EQ‐5D‐3L estimates.

Conclusions

Pooled estimates of health utility for stroke survivors were substantially below population averages. We provide reference values for health utility in stroke to support future clinical and economic studies and identify subgroups with lower healthy utility.

Registration

URL:
https://www.crd.york.ac.uk/prospero/
. Unique Identifier: CRD42020215942.
On the stream-dwelling Crossodactylus timbuhy (Anura, Hylodidae): taxonomy, natural history, and geographic distribution
Authors: LACERDA JOÃO VICTOR A. , MONTESINOS RACHEL , ZOCCA CÁSSIO , GUIMARÃES CARLA S. , SANTANA DIEGO J. , FERREIRA RODRIGO B.
Published: June 2022

The genus Crossodactylus has taxonomic problems due to the difficulty in properly identifying some populations to the species level. The deficient species diagnosis rises mostly due to high intraspecific variation and lack of information on topotypes. Crossodactylus timbuhy was described based only on external morphology of preserved adult specimens. Based on topotypic specimens, we provide further information on C. timbuhy regarding color in life (both adult and larvae), tadpole external morphology, vocal repertoire, natural history, and geographic distribution. The species identification was confirmed through comparison to the type series, 16S rRNA analysis, and bioacoustics. Crossodactylus timbuhy vocalizes during daylight along shallow slow-flowing streams. The advertisement call has ascendant amplitude modulation, duration of 2.1–8.4 s, 23–75 pulsed notes, and peak frequency of 3.6–4.8 kHz. Our report on male unilateral sac inflation is the first within Crossodactylus. Although overall tadpole external morphology and coloration resemble other species of hylodids, we report ventral depression and golden iridophores also for the first time within Crossodactylus. Adult males display five antipredator mechanisms (interrupt calling, escape, aggression, posture, and aposematism). Finally, we restrict its geographic distribution to the Municipality of Santa Teresa, State of Espírito Santo, Southeastern Brazil.
Platform and Device Neutrality Regime: The New Competition Rulebook for App Stores?
Authors: Borgogno Oscar , Colangelo Giuseppe
Published: June 2022

Among the numerous legislative initiatives implemented around the globe on digital platforms, some of these provisions are explicitly directed toward app stores. As they have all the distinctive features of multi-sided markets, app store owners represent the prototype of digital gatekeepers, controlling access to mobile ecosystems and competing with business users operating on the platforms. In light of the rule-setting and dual role of these gateway players, regulatory interventions are required in order to ensure that large app stores are treated like common carriers or public utilities, thereby imposing upon them a neutrality regime vis-à-vis new entrants. For the very same reasons, dominant app store providers have been subject to an increasing number of antitrust investigations attempting to ensure equal treatment and to avoid self-preferencing at the expense of rivals’ services. Against this background, the article investigates whether antitrust provisions are flexible enough to curb anticompetitive practices carried out by app stores and the extent to which regulatory interventions could, on the other hand, be necessary in order to address the seemingly unique features of the app economy.
Development and Validation of Occupation Based Practice Measure (OBPM)
Authors: Khayatzadeh-Mahani Mohammad , Hassani Mehraban Afsoon , Kamali Mohammad , Parvizy Soroor , Haghani Hamid , Amini Malek
Published: June 2022

Background. Occupation based practice (OBP) is the central core of occupational therapy. Therefore, measuring its usage and influencing factors seems necessary. Purpose. To develop and validate the occupation based practice measure (OBPM). Method. OBPM was developed in two phases: (I) following a qualitative study, a literature review was conducted. The item pool was revised by expert panel; (II) The face, content, construct validity, internal consistency, and test–retest reliability were assessed. Findings. The 142 items derived through the qualitative study were integrated with the 42 items derived from the literature review. The item pool was reduced by expert panel to 78 items and finalized to 37 items through face, content, and construct validity. Cronbach's alpha was greater than 0.70 and intra-class correlation coefficient showed good to excellent reliability. Implications. OBPM is a valid and reliable questionnaire that evaluates the occupational therapists’ knowledge, attitudes, interest, usage, and contextual factors influencing the OBP.
What Explains Caste-based Wage Inequalities and Earning Gaps in the Indian Labour Market? Theil and Oaxaca Decomposition Analysis
Authors: Gupta Pallavi , Kothe Satyanarayan
Published: June 2022

Caste-based wage discrimination can counteract the development process. This article uses two distinct estimation methods to examine earning gaps between forward castes also referred to as ‘general category’ workers and traditionally disadvantaged or ‘backward caste’ workers in the Indian labour market. First, we interpret the inequality indicator of the Theil index and decompose Theil to show within and between-group inequalities. Second, a Threefold Oaxaca Decomposition is employed to break earnings differentials into components of endowment, coefficient and interaction. Earning gaps are examined separately in urban and rural divisions. Within-group inequalities are found larger than between groups across variables, with a higher overall inequality for forward castes. Wage differentials are substantially greater for urban areas and favour FC. A high endowment implies pre-market discrimination in human capital investments such as nutrition and education. Policymakers should first invest in basic quality education and simultaneously expand postgraduate diploma opportunities, subsequently increasing participation in the labour force for traditionally disadvantaged in disciplines and occupations where forward castes have long dominated.

JEL Codes: J01, J08, J15, J30, J31, J71
Socioeconomic differences associated with consumption of a plant-based diet: Results from the national health and nutrition examination survey
Authors: Gonzalgo Mia R. , Nackeeran Sirpi , Mouzannar Ali , Blachman-Braun Ruben
Published: June 2022

Background

A plant-based diet (PBD) has been associated with potential health benefits, but factors that may affect access to and consumption of a PBD are not well defined.

Aim

To determine the association between socioeconomic status and plant-based dietary consumption among participants enrolled in the National Health and Nutrition Examination Survey (NHANES).

Methods

This was a cross-sectional study using data obtained from the NHANES database. The following covariates were assessed: age, sex, race/ethnicity, educational level, marital status, smoking status, physical activity, alcohol use, history of diabetes, and hypertension. Socioeconomic status was categorized according to poverty-income ratio (PIR). Food frequency questionnaires were used to calculate previously validated plant-based diet index (PDI) and healthful plant-based diet index (hPDI). Multivariable-adjusted logistic regression was performed to determine the association between PIR, clinical, demographic, and plant-based diet indices.

Results

A total of 5037 participants were in the final analytic sample. Median age of participants was 51 ± 18.5 years. Overall PDI and hPDI were 50 [46–54] and 52 [47–57], respectively. Median PDI index was significantly different among PIR groups (PDI, p = 0.018; hPDI, p < 0.001). On multivariable analysis, participants in the poorest socioeconomic group (PIR ≤ 130%) were more likely to have lower consumption of a healthful PBD (hPDI).

Conclusion

Lower socioeconomic status (PIR ≤ 130%) was associated with decreased consumption of a healthful plant-based diet. These data suggest that socioeconomic disparities may limit consumption of healthier food and contribute to the high prevalence of adverse health conditions that exist in certain population groups.
Social mobility or social change? How different groups react to identity-related news
Authors: Boyer Ming M , Lecheler Sophie
Published: June 2022

In times of identity politics, journalists use group primes to organize events and reduce their complexity. Because research has mostly investigated the effects of single group primes on opinion formation and news selection, two aspects of group primes in the news have remained understudied: (1) whether they directly affect group identification itself, and (2) how these effects differ between groups. This experiment ( N  =  750) shows that group primes in the news cause awareness of citizens’ membership in these groups. However, citizens’ perceived group importance diverges between groups: priming groups that likely have a social change mindset increases their perceived importance, while priming groups that likely have a social mobility mindset does not. Accordingly, the effects of group primes in the news depend on shared notions of a group's status in society and the rigidity of its boundary. These findings considerably advance contemporary understanding of differential news effects relating to group identification.
Inadequate human resources, equipment and training: A qualitative assessment of the objectives of the NUHELP end-of-life care programme in the context of the COVID-19 pandemic
Authors: Mota Romero Emilio , Puente Fernández Daniel , Rodríguez Pertíñez Carmen , Árbol Fernández Gema , Moreno Guerrero Socorro , Montoya Juárez Rafael
Published: June 2022

Background:

The COVID-19 pandemic had a particularly severe impact on nursing homes, exposing numerous pre-existing deficiencies in end-of-life care.

Aim:

To describe how the COVID-19 pandemic affected nursing home and primary care professionals’ attempts to achieve the objectives of a pre-existing end-of-life programme and to explore their personal experiences of end-of-life care in these facilities.

Design:

A qualitative descriptive study using thematic analysis.

Setting/participants:

Twenty semi-structured interviews were conducted from March to November 2020 with professionals from nursing homes and primary care facilities who participated in the development of the NUHELP programme.

Results:

Six main themes were identified: (1) Comprehensive assessments of residents at the homes were not conducted due to excessive workload and high staff turnover. (2) New technologies and changes to professional roles were used to meet relatives’ needs for information. Residents only received information when they requested it. (3) Advance care planning was not carried out and was limited to potential hospital transfer. (4) Arrangements were made to allow relatives to spend time with residents during their final moments, but complicated grief among relatives and professionals is anticipated. (5) Management of complexity varied depending on the degree of coordination with primary care facilities. (6) Nursing home professionals felt abandoned, with a lack of human resources, equipment and training.

Conclusions:

The pandemic cast light on existing shortcomings in nursing homes in terms of comprehensive assessments, communication, decision making, grief management and palliative care complexity. Nursing homes need more human, material and training resources, as well as improved coordination with the public healthcare system.
Usefulness of subtraction images for accurate diagnosis of pituitary microadenomas in dynamic contrast-enhanced magnetic resonance imaging
Authors: Taheri Morteza Sanei , Ghomi Zahra , Mirshahi Reza , Moradpour Moein , Niroomand Mahtab , Yarmohamadi Parsa , Zeidabadi Hamideh
Published: June 2022

Background

Dynamic contrast-enhanced magnetic resonance imaging (MRI) is the modality of choice for the diagnosis of pituitary microadenomas; however, it may be associated with a relatively high false-negative rate, especially in small lesions.

Purpose

To evaluate the usefulness of subtraction images for enhancing the visual detection of pituitary microadenomas.

Material and Methods

In total, 50 patients with clinically established diagnosis hyperprolactinemia, acromegaly, and Cushing's disease were enrolled. Ten patients referred for brain MRI for reasons other than pituitary abnormality were selected as control group. Routine dynamic MRI of the pituitary gland and obtained subtraction MRI scans were scrutinized separately on different sessions by an experienced radiologist blinded to the study design and patient's data. The investigator's opinion on the presence or absence of a lesion and lesion size were collected.

Results

In patients with pituitary microadenoma, dynamic MRI images were reported positive in 42 (84%) patients and negative in 8 (16%). Subtraction images were described as positive in all patients (100%)—including all patients with negative dynamic MRI—and the difference was statistically significant ( P=0.016). Undetected lesions on dynamic MRI had a mean size of 2.84 ± 1.79 mm (median= 2.20 mm, interquartile range=1.62–4.62 mm) and a significant inverse correlation was noted between lesion size and negative report of dynamic MRI ( P=0.018). Brain MRI scans in the control group were reported negative for pituitary microadenoma in both dynamic contrast-enhanced and subtraction images.

Conclusion

Subtraction images can successfully identify all lesions detectable with conventional dynamic MRI as well as improving visualization of lesions undetected on dynamic MRI, especially in small lesions.
Correlation between C-reactive protein/albumin ratio and prognosis in patients with lung adenocarcinoma
Authors: Jia-min Zheng , Wei Dai , Ye Lu , Xiang-tao Pan
Published: June 2022

Objective

This study was performed to examine the relationship between the C-reactive protein/albumin ratio (CAR) and the prognosis of patients with lung adenocarcinoma and thus provide a reference for evaluating the prognosis of lung adenocarcinoma.

Methods

The clinical data of 130 patients with lung adenocarcinoma were retrospectively collected and analyzed. The patients’ overall survival (OS) time was calculated, and the factors affecting OS were statistically analyzed.

Results

The CAR was correlated with sex, clinical stage, brain metastasis, S100 calcium-binding protein B (S100B), interleukin 17, myelin basic protein, squamous cell carcinoma antigen (SCC-Ag), and the lymphocyte count. The median OS was significantly shorter in the high- than low-CAR group (18 vs. 64 months, respectively). The CAR, clinical stage, brain metastasis, S100B, interleukin 17, SCC-Ag, C-reactive protein, albumin, and neutrophil count affected the OS of patients with lung adenocarcinoma. The CAR and clinical stage were independent risk factors for a poor prognosis in patients with lung adenocarcinoma.

Conclusions

The CAR and clinical stage are independent risk factors for OS in patients with lung adenocarcinoma.
Explaining the Patterns of Bullying Victimization Trajectories: Assessing the Generality of Low Self-Control and Crime Opportunity Models to Bullying Victims
Authors: Cho Sujung , Park Insun
Published: June 2022

This study hypothesizes that self-control and opportunity variables affect heterogeneity in developmental trajectories of bullying victimization. Using data from a follow-up study of 2,351 Korean adolescents, the study incorporates a latent class growth analysis approach to identify subgroups, each with a unique pattern of the trajectories. The model yields three subgroups of bullying victims: the early-onset and decreaser, the increaser and late-peak, and the normative groups. Results suggest that, compared to the normative group, the early-onset and decreasing group members manifest lower levels of self-control and engage in a greater range of delinquent behaviors. Also, the impact of low self-control on group membership was attenuated after controlling for those opportunity variables, indicating a partially mediating relationship. Social guardianship variables distinguished normative groups from other victim groups. Further, members of the increaser and late-peak group were more likely than the early-onset and decreaser group members to engage in cyber deviance over the long-term.
Manual for Assessing Safety Hardware TL-4 Evaluation of Critical Flare Rate for Cast-in-Place Concrete Barrier
Authors: Kiani Maysam , Dobrovolny Chiara Silvestri , Bligh Roger , Lindsey Chris
Published: June 2022

Concrete median barriers are used by Departments of Transportation (DOTs) to provide separation of traffic. Typically, the crashworthiness of these barriers is tested and evaluated in full-scale crash testing conducted according to current roadside safety device standards. Occasionally, DOTs need to flare the concrete barrier length of need (LON) around fixed objects, such as bridge piers. Flaring a concrete barrier increases the effective impact angle which consequently increases the impact severity of the vehicle creating an opportunity for vehicle instability or excessive occupant risk factors. No current recommendations are available to guide the installation of flared barriers around such fixed objects, while still maintaining barrier crashworthiness. Although the current practice is to flare the cast-in-place (CIP) concrete barrier at a maximum 20:1 rate, no full-scale crash testing has been conducted to determine the crashworthiness of the system at this condition or at a flare rate that might be considered more critical. The crash tests reported in this paper were performed according to the Manual for Assessing Safety Hardware (MASH) Tests 4–10 (with the use of a passenger car), 4–11 (a pickup truck), and 4–12 (a single unit truck) for LON, which represent the tests considered necessary to demonstrate the MASH compliance of the device. The 40-in. single slope CIP concrete barrier with a 20:1 flare rate met MASH requirements and is considered MASH compliant for Test Level (TL) 4. The system is considered suitable for implementation where there is a need to flare the concrete barrier around a fixed object.
The Women's National Abortion Action Coalition & the Abortion Tribunals, 1971–1972
Authors: Parkin Katherine
Published: June 2022

The Women's National Abortion Action Coalition organized for abortion rights, an end to forced sterilization, and accessible birth control. From its formation in July 1971 to its demise with the January 1973 Roe v. Wade decision, it was an inclusive, far-reaching network that spearheaded the call for reproductive justice. Assembling a coalition, including high school and college students and those who called themselves Third World women (Black, Hispanic, Asian, and Native American women), the group held marches, protests, and in the fall of 1972 abortion tribunals across the country, holding men in power accountable for the oppression of women.
Minimally invasive ureterolysis and intraperitonealization of ureter for idiopathic retroperitoneal fibrosis; single center analysis of an erratic disease
Authors: Batra Vikram Shah , Singh Mahendra , Kathuria Sachin , Jain Saurabh , Rasool Shahnawaz , Gupta Manu , Pandey Himanshu , Sharma Ajay
Published: June 2022

Introduction

Idiopathic retroperitoneal fibrosis is a known cause of obstructive uropathy. Ureterolysis is done when medical management fails or the presentation is at an advanced stage. Conventionally ureterolysis without omental wrap has been considered incomplete. Our Institute has experience of laparoscopic or robotic ureterolysis with intraperitonealization of the ureter alone and no other adjunctive procedure. This study retrospectively assesses the result of the procedure with patients presenting with varying severity of disease.

Methods

From 2008, all patients who underwent laparoscopic or robotic ureterolysis were analyzed retrospectively for pre-operative management, operative findings, and post operative outcomes.

Results

We operated and released nine renal units in seven patients. Two of the nine cases were performed robotically completely and the rest was performed by laparoscopic approach. Median follow up was 60 months. All patients documented resolution of symptoms. The mean post-operative creatinine at 1 year was significantly decreased to 1.47 ± 0.49 mg/dl in comparison to preoperative creatinine ( p < 0.05). The postoperative mean ESR decreased significantly from a preoperative value of 58.2 ± 19.41 mm to 15.8 ± 17.23. The nuclear scan revealed unobstructed drainage and radiological imaging revealed resolution of hydronephrosis and fibrosis in all. The mean GFR on the nuclear scan after 3 and 12 months of surgery was 36.3 ± 4.33 and 40 ± 3.77, respectively. Thus, there was significant increase noted in GFR at 3 and 12 months in comparison to preoperative GFR ( p < 0.05).

Conclusion

Laparoscopic/robotic ureterolysis with intraperitonealization alone is secure and durable procedure for idiopathic retroperitoneal fibrosis needing surgical release.
Motivating Positive Youth Outcomes Through Proximal, Relevant, and Attainable Inspirational Figures
Authors: Quinn Johanna S. , Roberts E. Danielle , Chen Wei-Lin , Doubledee Rachael , Brown Urban Jennifer , Linver Miriam R.
Published: June 2022

This paper focuses on data from a study of middle- to upper-middle class Scottish S2 (~seventh grade) students who participated in Inspiring Purpose, a school-based character development program, during the 2016 to 2017 school year. Directed by their teachers, participating youth reflected on values and future aspirations and researched and wrote about an inspiring person. We examine the hypotheses that youth who select a more proximal inspiring figure and/or make a personal connection with that person will demonstrate higher developmental outcomes in the areas of confidence, contribution, self-reflection, goal development, and self-concept. We connected 230 student posters of inspirational figures, 34 youth interviews, and 462 student surveys. Mixed-method analysis revealed students were more likely to describe proximal figures as inspiring and make explicit personal connections over the course of their engagement with the Inspiring Purpose program. Moreover, youth who made personal connections were more likely to score higher on confidence, general self-concept, and contribution. These results suggest that when youth see themselves in inspiring figures and firmly articulate this connection, this can spur beneficial developmental outcomes.