Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of Participatory Action Research in Reviving Endogenous Rangeland Management: A Case from Southern Ethiopia

African rangelands are extensive and support large populations of pastoral people and livestock. The semi-arid Borana Plateau is an especially important rangeland for Ethiopia. It is over 95,000km 2 in size and home to about 350,000 people and one million head of cattle, small ruminants, and camels. The grazing systems of the Borana Plateau have become increasingly unsustainable in recent decades, however, because of human population growth, expansion of maize production in dry-season grazing areas, and range degradation in the form of woody encroachment. Heavy grazing by livestock, reduced mobility of pastoralists, and lack of fire have contributed to conversion of open, mixed savannah communities to dense woodlands and bushlands. Herbaceous forage production for cattle and sheep can then be reduced via competition with woody plants for water and light. Residual grass can be subjected to intense grazing pressure, further exacerbating the downward spiral. Prescribed fire is the most cost-eective means of manipulating vegetation in savannah ecosystems of eastern Africa. A blanket national ban on the use of fire was initiated in Ethiopia during the 1970s. This was intended to protect croplands and other natural resources from indiscriminant burning, but one unintended consequence of this policy has been a weakening of traditional forms of range management that depended, in part, on the regulated use of fire to control undesirable woody plants, promote herbaceous forage production, and reduce populations of disease-carrying ticks. Eorts by pastoral communities to revive endogenous range management practices like the use of fire are now gaining the positive attention of policy makers. An alliance among pastoral communities, researchers, policy makers, and development actors is being forged to re-introduce prescribed fire to the Borana Plateau. Describing this process is the objective of this paper. The process requires a combination of indigenous knowledge, modern technology, training, and research, as well as creation of a truly collaborative management approach. Rather than topdown research, the key elements for change have been participatory action research, outreach, and engagement with a wide variety of stakeholders.
Isolation Without Taxation: Near Zero Cost Transitions for SFI

—Almost all SFI systems use heavyweight transitions that incur signiﬁcant performance overhead from saving and restoring registers when context switching between application and sandbox code. We identify a set of zero-cost conditions that characterize when sandboxed code is well-structured enough so that security can be guaranteed via lightweight zero-cost transitions. We show that using WebAssembly (Wasm) as an intermediate representation for low-level code naturally results in a SFI system with zero-cost transitions, and modify the Lucet Wasm compiler and its runtime to use zero-cost transitions. Our modiﬁcations speed up image and font rendering in Firefox by up to 29.7% and 10% respectively. We also describe a new purpose-built fast SFI system, SegmentZero32 , that uses x86 segmentation and LLVM with mostly off-the-shelf passes to enforce our zero-cost conditions. While this enforcement incurs some runtime cost within the sandboxed code, we ﬁnd that, on Firefox image and font rendering benchmarks, the time saved per transition allows SegmentZero32 to outperform even an idealized hardware isolation system where memory isolation incurs zero performance overhead but the use of heavyweight transitions is required.
A Deep Learning Model Based on Capsule Networks for COVID Diagnostics through X-ray Images

X-ray diagnostics are widely used to detect various diseases, such as bone fracture, pneumonia, or intracranial hemorrhage. This method is simple and accessible in most hospitals, but requires an expert who is sometimes unavailable. Today, some diagnoses are made with the help of deep learning algorithms based on Convolutional Neural Networks (CNN), but these algorithms show limitations. Recently, Capsule Networks (CapsNet) have been proposed to overcome these problems. In our work, CapsNet is used to detect whether a chest X-ray image has disease (COVID or pneumonia) or is healthy. An improved model called DRCaps is proposed, which combines the advantage of CapsNet and the dilation rate (dr) parameter to manage images with 226 × 226 resolution. We performed experiments with 16,669 chest images, in which our model achieved an accuracy of 90%. Furthermore, the model size is 11M with a reconstruction stage, which helps to avoid overfitting. Experiments show how the reconstruction stage works and how we can avoid the max-pooling operation for networks with a stride and dilation rate to downsampling the convolution layers. In this paper, DRCaps is superior to other comparable models in terms of accuracy, parameters, and image size handling. The main idea is to keep the model as simple as possible without using data augmentation or a complex preprocessing stage.
System for Identification of Voice Calls of Interest in a Telecom Communication Network

In recent times, there has been a huge increase in the number of value-added services being provided to end customers. This has been further complemented by the advancement in telecommunication services including the introduction of 5G and associated services provided by communication service providers (CSPs) or Over the Top (OTT) applications vendors. As a result of this increase in services, different targeted marketing campaigns are used by various vendors to approach the end customers through different communications channels e.g., voice, data, SMS, USSD, etc. Specifically, amongst these, marketing through voice channels is important considering it to be a more real-time communication where the end-users need to act (accept or reject the call) in a specific time to establish the communication, unlike SMS wherein response can be more asynchronous. Considering the above, it becomes even more important for the end-users to identify if the received voice call is of interest to the user or is a Spam call. This has been a long-standing problem to accurately distinguish between Spam calls and ‘Call of Interest’. ‘Call of Interest’ may refer to a voice call that the end-user would not like to miss but it may be from someone not available in saved contacts (e.g., a response call from a repair agency that was contacted earlier by the end-user). Various methods are available in the state of the art to solve the said problem; however, those may not be sufficient to accurately identify the ‘Call of Interest’. As mentioned, there can be instances wherein the call may be a Spam call for a set of users however it may be of interest to another user. Accurate identification of such a ‘Call of Interest’ is the focus of this paper.
Recent Advances and Sustainable Approaches Towards Efficient Wastewater Treatment Using Natural Waste Derived Nanocomposites: A Review

Pollutants like arsenic, chromium, or other toxic heavy metals have the most dreadful impact on humans or animals and also become a threat worldwide. Introducing these contaminants into the environment is not just due to the chemical industry but also coexists in combined form in underground rocks, contaminating groundwater during breakdown. Epidemics are now largely blamed on toxic pollution in many different nations worldwide. The issue has gotten worse in underdeveloped nations, where metal contamination of the groundwater affects more than a million people. Different techniques are used to remove toxic pollutants from water, but most are expensive and energy intensive. Adsorption is preferable for removing contaminants such as heavy metals or chemical dyes. As nanomaterials have been demonstrated to be more effective as nanocomposites, we used an adsorbent of nanomaterial to use the adsorption approach. These materials have become more well-liked because of their useful applications and improved characteristics. Magnetic synthesized nanocomposites have magnetic properties, which become beneficial for adsorption as it enhances adsorption capacity. The insertion of the plant or aggregate waste material for nanocomposite synthesis inhibits the growth of bacteria or other microorganisms, preventing the material from getting infected if it is in the environment. In this review paper, we have focused on the green synthesis of nanomaterials used for water treatment.
The Effect of Coronal Pre-flaring and Type of Root Canal Irrigation on Working Length Accuracy Using Electronic Apex Locators

Background: Successful root canal treatment is influenced by the apical extent of root canal preparation and the eventual root canal filling. Achieving the full working length until the apical constriction, which is usually 0.5 – 1 mm shorter than the anatomical apex, is crucial. Electronic apex locators were used to detect the working length more accurately. There are six generations of electronic apex locators in the market. The selection of the appropriate irrigation with each apex locator for accurate working length determination is not fully investigated. Methods: The actual working lengths of 120 freshly extracted human single-rooted teeth were measured and compared with their working lengths using 3 rd generation (Root ZX) followed by 6 th generation (Raypex 6) apex locators in dry medium, presence of 5.25% sodium hypochlorite, and 2% chlorhexidine, without coronal pre-flaring and after coronal pre-flaring using the same irrigating media. Data were collected, tabulated, and afterward analyzed using one-way ANOVA with post-hoc to evaluate the significant difference in average working length between actual working length, Root ZX, and Raypex 6 apex locator working lengths accuracy. Results: The significant results were shown in roots that were coronally pre-flared and their working lengths were measured in a dry medium using Raypex 6 apex locator. While using the Root ZX apex locator, the most accurate results were shown in roots that were coronally pre-flared and their working lengths were measured while using a chlorhexidine irrigating solution. Conclusions: It is concluded that it is very important to know the specific irrigating medium to be used with each specific electronic apex locator to achieve the most accurate working length results.
Reducing Pilot Overhead for Channel Estimation in RIS-assisted Millimeter-wave Systems

The reconfigurable intelligent surface (RIS) is a potential technology to enhance millimeter wave (mmWave) coverage due to its low hardware cost and low power consumption. By reconfiguring the RIS elements according to the surrounding environment, it is possible to achieve high beamforming gain. However, for reliable beamforming, accurate channel state information (CSI) is required. In general, the channel estimation task is non-trivial as RIS is passive and cannot transmit, receive, or process signals. Moreover, due to a large number of RIS elements, the required pilot overhead will be very large. In this paper, we propose an algorithm to reduce the pilot overhead associated with channel estimation. Assuming symmetrical propagation conditions, we are able to show that the pilot overhead can be reduced by half. Numerical results and Monte Carlo simulations verify our analysis.
A Robust Approach for Malware Attacks Detection in the Internet of Things Communications

The detection of malicious software is an essential activity for ensuring the ongoing security of the Internet of Things (IoT). Malware, often known as malicious software, is computer code designed to steal private information, corrupt data or files, or otherwise interfere with the functioning of a computer system. A number of different methods, including signature-based detection, heuristic analysis, and behaviour-based detection, are utilised in the process of identifying malicious software. The process of searching for specific patterns or signatures that are characteristic of known malware is what is referred to as signature-based detection. The success of this method is dependent on the upkeep of a database containing known malware signatures. Heuristic analysis, on the other hand, uses rules and algorithms to detect suspicious behaviour that may indicate the presence of malware. This approach does not rely on specific signatures but instead analyzes the code or behaviour of a file or program. If the behaviour exhibits characteristics commonly associated with malware, it is flagged as potentially malicious. Behaviour-based detection focuses on analyzing the behaviour of software programs to identify anomalous or malicious activity. Utilizing machine learning algorithms for malware detection helps to identify potential threats and prevent them from compromising valuable data and information. In this paper, we propose a robust approach for the detection and analysis of malware attacks in the communications of the IoT. In the proposed protocol various machine learning-based models, i.e., k-nearest neighbours (KNN), random forest and neural networks are used. The proposed protocol is also compared with the other similar existing protocols and it has achieved better accuracy as compared to the other existing protocols.
First report on diversity and relative abundance of questing and feeding hard ticks (Acari: Ixodidae) of the tribal communities and wildlife in Aralam Wildlife Sanctuary of Western Ghats, Kerala, India

ABSTRACT The present study is the first report on ticks infesting domestic animals of the tribal communities and wildlife in Aralam Wildlife Sanctuary, Kerala, India. Questing ticks in the sanctuary were collected through dragging methods and hand collection from domestic animals was used to collect feeding ticks. Among the total 3,081 ticks collected, 2,350 questing ticks were obtained from the forest floor, and 731 ticks were recorded from 40 different domestic animals belonging to four species. The present collection recorded eight Haemaphysalis species: Ha. spinigera, Ha. leachii, Ha. shimoga, Ha. kinneari, Ha. kyasanurensis, Ha. turturis, Ha. bispinosa, Ha. intermedia and one Amblyomma species: Am. integrum from the sanctuary. Whereas five Haemaphysalis species: Ha. bispinosa, Ha. intermedia, Ha. shimoga, Ha. spinigera, Ha. turturis and four Rhipicephalus species: Rh. sanguineus, Rh. haemaphysaloides, Rh. microplus and Rh. annulatus were reported from domestic animals. High abundance of Kyasanur Forest Disease (KFD) vectors, Ha. spinigera and Ha. turturis have been documented from the sanctuary. Relative abundance of Ha. bispinosa was significantly higher in all the domestic animals examined. Tick infestation rate was higher in goats followed by cows, dogs, and cats. Whereas the species richness of ticks was highest in cows and lowest in cats.
Escherichia coli Phylogenetic and Antimicrobial Pattern as an Indicator of Anthropogenic Impact on Threatened Freshwater Mussels

Freshwater bivalves are widely used as accumulation indicators and monitoring tools for assessing contaminant effects on different levels of biological integration. This pilot study aimed to explore the phylogenetic diversity of Escherichia coli isolated from freshwater mussels (Margaritifera margaritifera and Potomida littoralis) and characterize their phenotypes and antibiotic resistance profiles. Samples were collected in the Rabaçal and Tua Rivers, in the Douro basin, Portugal—two sites representing different levels of anthropogenic contamination. Antimicrobial susceptibility testing was performed via the disk diffusion method with 21 antibiotics. Results showed that 31% of isolates were multidrug-resistant (MDR). Thus, freshwater mussels provide an effective and time-integrated approach for identifying/quantifying fecal indicators, including MDR bacteria. PCR-based assays were designed for assessing phylogenetic E. coli groups. Among the E. coli isolates, the highest prevalence (44%) was observed in group D or E, followed by group E or Clade I (25%), group A (19%), and group B1 (13%). E. coli isolated from M. margaritifera predominantly exhibited a higher prevalence of phylogroups D or E, whereas E. coli from P. littoralis showed associations with phylogroups E or clade I, B1, A, and D or E. Our results provide new insights into the phylogenetic diversity of E. coli in freshwater bivalves. Additionally, the findings highlight the possible linkage of phylogroups with the host species, the geographical location in the water stream, and human activity. Using E. coli as a bioindicator isolated from freshwater mussels helps us grasp how human activities affect the environment. This study has important implications for those interested in safeguarding water resources, especially in tackling antibiotic resistance in aquatic ecosystems.
Laser-Induced Nonthermal Spin Dynamics in Ferromagnetic Materials Probed by Ultrafast Magneto-Optic Spectroscopy

Demagnetization of ferromagnets initiated by pulsed laser has attracted attention due to ultrafast magnetism quenching within less than a picosecond timescale. The mechanisms for demagnetization have been discussed for a long time and most discussions have focused on secondary processes with angular momentum dissipation [1] and thermal processes [2].
Nurses’ view of benefits, enablers and constraints to the use of digital health tools with patients: A cross-sectional study

Introduction Digital literacy helps patients to be more informed in order to make decisions about their health. Patient empowerment in the digital realm is a duty for all healthcare professionals, but nurses are the most numerous professionals in all healthcare systems worldwide. In addition, they have an important role in health education and patient follow-up. Therefore, the use of digital tools, by nurses to empower and help patients know more about their health, is crucial. Objective This study was conducted to identify nurses’ views on the benefits as well as constraints nurses encounter when using digital resources to empower and educate their patients. We sought to identify enablers that could help nurses use technology with their patients as a means to reinforce the care and advice they offer them. Methods An online ad hoc questionnaire was answered by 848 currently employed Spanish nurses on the benefits of using digital media with their patients, as well as on the constraints and enablers during implementation. Results The majority of the nurses considered that reliable digital information would reduce unnecessary consultations. In addition, they think that at least 50% of their patients could benefit from consulting information online. Among the constraints, nurses mainly pointed out the older age and low educational level of their patients. Younger nurses are the most likely nurses to see patient age as a problem. As for enablers, nurses pointed out the training offered to patients as well as digital tools being user-friendly for patients. Conclusions It is crucial to work while following a lifelong learning strategy, with training from university education as well as training from healthcare institutions to reduce the digital gap that affects patients’ digital empowerment.
Antidiabetic Molecule Efficacy in Patients with Type 2 Diabetes Mellitus—A Real-Life Clinical Practice Study

In this paper, we aim to evaluate the efficacy of antidiabetic cardioprotective molecules such as Sodium-Glucose Cotransporter-2 Inhibitors (SGLT-2i) and Glucagon-like Peptide 1 Receptor Agonists (GLP-1 RAs) when used with other glucose-lowering drugs, lipid-lowering, and blood pressure (BP)-lowering drugs in a real-life setting. A retrospective, observational study on 477 patients admitted consecutively in 2019 to the outpatient clinic of a tertiary care unit for Diabetes Mellitus was conducted. Body mass index (BMI), blood pressure (BP) (both systolic and diastolic), and metabolic parameters, as well as A1c hemoglobin, fasting glycaemia and lipid profile, including total cholesterol (C), HDL-C, LDL-C and triglycerides), were evaluated at baseline and two follow-up visits were scheduled (6 months and 12 months) in order to assess the antidiabetic medication efficacy. Both SGLT-2i and GLP-1 RAs were efficient in terms of weight control reflected by BMI; metabolic control suggested by fasting glycaemia and A1c; and the diastolic component of BP control when comparing the data from the 6 and 12-month visits to the baseline, and when comparing the 12-month visit to the 6-month visit. Moreover, when comparing SGLT-2i and GLP-1 RAs with metformin, there are efficacy data for SGLT-2i at baseline in terms of BMI, fasting glycaemia, and HbA1c. In this retrospective study, both classes of cardioprotective molecules, when used in conjunction with other glucose-lowering, antihypertensive, and lipid-lowering medications, appeared to be efficient in a real-life setting for the management of T2DM.
Faculty of Sports Sciences Students' Opinions on the Community Service Practice Course

Educational institutions play a major role in meeting social needs and expectations. Particularly, the Community Service Practices (CSP) course within universities offers students the opportunity to engage in social activities with the community, to gain awareness of social responsibility, and to get to know the community from different perspectives. For this reason, this research was carried out to determine the opinions of the Faculty of Sport Sciences students who took the 'Community Service Practices' course before taking it and their gains after the course. A total of 53 students who were studying at Bolu Abant İzzet Baysal University Faculty of Sports Sciences and taking Community Service Practices course participated in the research. The research was applied in two parts as before and after the application. Before the application, the students were asked about their expectations about the CPS course in the form of open-ended questions and their answers were requested in writing. At the end of the application process, 14 people were determined to participate in the interview voluntarily, and focus group interviews were held with semi -structured questions. The questions directed to the students were recorded using the note-taking technique. The data obtained from the students' opinions were coded independently by two researchers by making descriptive and content analysis. As a result of the research, it is observed that the students show positive progress in terms of social awareness, social responsibility, communication, professional experience and cooperation with the CPS course in the university programs.
Polycyclic Aromatic Hydrocarbons in Thai and Myanmar Rice: Concentrations, Distribution and Health Concerns

In the present study, we studied the concentrations and proportions. We identified the potential sources and health risks of 12 probably carcinogenic polycyclic aromatic hydrocarbons (PAHs) in rice grain from 31 sites in Thailand and Myanmar. The findings showed that PAH concentrations in rice grain samples from Thailand and Myanmar were in the range of 0.09 to 37.15 ng.g-1 with an average value of 18.22 ± 11.76 ng.g-1 and 0.07 to 150.73 ng.g-1 with an average value of 34.70 ± 40.57 ng.g-1, respectively. The majority group of PAHs in the rice grain samples from Thailand were the five-ring PAHs (78%), followed by four-rings (12%) and three-ring PAHs (9.5%), respectively, while for Myanmar was the five-ring PAHs were the majority (64.02%), followed by six-rings (15.22%) and four-ring PAHs (13.58%), respectively. The diagnostic ratio analysis suggested that pyrogenic origin is a major source of PAHs, and principal component analysis (PCA) identifies the incomplete combustion of fuel as likely the primary source of emissions source of PAHs contamination in rice grain samples. The total values of incremental lifetime cancer risk (ILCR) of PAH content of rice grain for children and adults were 1.95 × 10-8 and 1.44 × 10-8, respectively, for Thailand and 1.83×10-7 and 1.35×10-7 for Myanmar, which showed that the incremental lifetime cancer risk from rice grain was lower than the baseline set is considered to be safe levels.