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Meta Data Fields and Details This dataset contains detailed metadata about rape cases reported in Bangladesh during the year 2013-2023. The dataset is intended for researchers, policymakers, and organizations focused on understanding and addressing sexual violence. It includes information on the circumstances of each incident, the legal proceedings, the conditions of the victims, and the responses from the police and community. Each entry in the dataset provides a wealth of information that can be used for in-depth analysis and research. The metadata includes fields such as: Total Sample Size: This dataset comprises a total of 2,813 rows, each representing an individual case reported in various districts across Bangladesh. Temporal Coverage: Minimum Date: February 22, 2013 Maximum Date: April 10, 2023 Data Description: incident_details: A description of the incident, including key events and actions taken by the perpetrators. legal_proceedings: court: The name of the court handling the case. judge: The name of the judge presiding over the case. confession_date: The date when the confession was made. confession_details: Details about the confession given by the accused. victim_education_status: The education status of the victim (e.g., student, graduate). location: district: The district where the incident occurred. upazila: The sub-district or upazila where the incident occurred. road: The specific road or location within the district. victim_condition: The condition or status of the victim (e.g., stable, critical, student). is_fatal_weapon_used_in_rape: Indicates whether a fatal weapon was used in the incident (true/false). police_response: Details about the actions taken by the police in response to the incident. is_romantic_relationship: Indicates whether the incident involved a romantic relationship between the victim and the perpetrator (true/false). time_of_incident_hour: The hour when the incident occurred, if available. attacker_details: Information about the attackers, including names, ages, aliases, occupations, and residences. local_leaders_involved_in_arbitration: Indicates whether local leaders were involved in arbitration (true/false). pressure_from_attackers_family: Details about any pressure exerted by the attacker's family on the victim or their family. medical_response: Details about the medical response provided to the victim (e.g., medical examination, autopsy). community_response: Details about the community's response to the incident. is_pressure_from_attackers_family: Indicates whether there was pressure from the attacker's family (true/false). date_of_incident: The date when the incident occurred. legal_perspective: Legal perspective or interpretation related to the incident, if available. is_victim_family_filed_complaint_by_themselves: Indicates whether the victim's family filed the complaint themselves (true/false). victim_age: The age of the victim. police_involvement: Details about the involvement of the police in the case. outcome_of_arbitration: The outcome of any arbitration involving local leaders. officer_in_charge: The name of the officer in charge of the case. victim_marital_status: The marital status of the victim. victim_action: Actions taken by the victim in response to the incident (e.g., filing a complaint). number_of_attackers: The number of attackers involved in the incident. police_statement: Statements given by the police regarding the incident. motive_behind_not_filing_complaint: The motive behind not filing a complaint, if applicable. time_of_incident: The specific time of the incident, if available. public_response: The response of the public to the incident. Example Meta Data Entry { "incident_details": "The victim was abducted, raped, and murdered by Krishna Chandra Das with the help of his three friends. The body was disposed of in a sack by the roadside.", "legal_proceedings": { "court": "Tangail Chief Judicial Magistrate Court", "judge": "Senior Judicial Magistrate Md. Ariful Islam", "confession_date": "Sunday", "confession_details": "Krishna Chandra Das and his three friends confessed to the abduction, rape, and murder of the school student." }, "victim_education_status": "SSC examinee", "location": { "district": "Tangail", "upazila": "Bhuyapur", "road": "Tarakandi road" }, "victim_condition": "School student", "is_fatal_weapon_used_in_rape": true, "police_response": "Tangail Police Bureau of Investigation (PBI) conducted raids and arrested the four accused.", "is_romantic_relationship": true, "time_of_incident_hour": null, "attacker_details": [ { "name": "Krishna Chandra Das", "age": 28, "alias": "Sani Ahmed", "occupation": "Salon worker", "residence": "Bhengula village, Gopalpur upazila" }, { "name": "Sourav Ahmed", "age": 23, "residence": "Ispinjarpur village, Dhanbari upazila" }, { "name": "Mehedi Hasan", "age": 28, "residence": "Ispinjarpur village, Dhanbari upazila" }, { "name": "Mizanur Rahman", "age": 37, "residence": "Ispinjarpur village, Dhanbari upazila" } ], "local_leaders_involved_in_arbitration": null, "pressure_from_attackers_family": null, "medical_response": "The body was recovered and an autopsy was conducted.", "community_response": null, "is_pressure_from_attackers_family": false, "date_of_incident": "Monday", "legal_perspective": null, "is_victim_family_filed_complaint_by_themselves": true, "victim_age": null, "police_involvement": null, "outcome_of_arbitration": null, "officer_in_charge": "Mohammad Siraj Amin", "victim_marital_status": null, "victim_action": null, "number_of_attackers": 4, "police_statement": "The accused have confessed to the crime in court." }

Populations change due to a combination of migration, births and deaths. Population change is the difference between all new residents in Idaho, including babies born and people moving in, and those who died or moved away. Population totals are estimates by the U.S. Census Bureau based on census counts, household surveys and other government data. These estimates are updated annually using new data and every decade based on census counts.

or decades, researchers on Vehicular Ad-hoc Networks vehicular ad-hoc networks (VANETs)
and autonomous vehicles presented various solutions for vehicular safety and autonomy,
respectively. Yet, the developed work in these two areas has been mostly conducted in
their own separate worlds, and barely affect one- another despite the obvious relation-
ships. In the coming years, the Internet of Vehicles Internet of Vehicles (IOV), encom-
passing sensing, communications, connectivity, processing, networking, and computation
is expected to bridge many technologies to offer value-added information for the navi-
gation of self-driving vehicles, to reduce vehicle on board computation, and to deliver
desired functionalities. Potentials for bridging the gap between these two worlds and
creating synergies of these two technologies have recently started to attract significant
attention of many companies and government agencies. We present a comprehensive
survey and an overview of the emerging key challenges related to the two worlds of Ve-
hicular Clouds (VCs) including communications, networking, traffic modelling, medium
access, VC Computing Vehicular Cloud Computing (VCC), VC collation strategies, secu-
rity issues, and autonomous driving Autonomous Driving (AD) including 3D environment
learning approaches and AD enabling deep-learning, computer vision and Artificial Intel-
ligence Artificial Intelligence (AI) techniques. We then discuss the recent related work
and potential trends on merging these two worlds in order to enrich vehicle cognition of
its surroundings, and enable safer and more informed and coordinated AD systems.
Modern vehicles are equipped with advanced communication, computation and storage
capabilities in On-Board Units (OBUs), that are used to form a Vehicular Cloud Vehicular
Cloud (VC) as coalitions of affordable resources to host infotainment applications. With
the limitation of static vehicular communication schemes and the computational capa-
bilities constraints in vehicular micro-datacenter, VCs have overcome these technological
limitations. VCs are supposed to maximize the usage of Vehicle to Infrastructure (V2I)
communications over Service Channels (SCHs) for non-safety applications while
maintaining reliable short-lived safety applications Vehicle to Vehicle Vehicle-to-Vehicle (V2V)
communications in the Dedicated Short Range Communication (DSRC) technology. We
present a novel Advanced Activity-Aware (AAA) scheme to enhance Multi-Channel Oper-
ations based on IEEE 1609.4 standard in MAC Protocol implemented in Wireless Access
in Vehicular Environments Wireless Access for Vehicular Environment (WAVE). The
developed AAA scheme relies on the awareness of the vehicular safety load. It aims at dy-
namically finding an optimal setup for switching between Service Channel Interval (SCHI)
and Control Channel Interval (CCHI) by decreasing every inactivity in the network. Our
scheme is implemented using NS3 and maintains the default Synchronization Interval
Synchronization Interval (SI), as defined by the standard in Vehicular Ad hoc Networks
(VANETs).
In addition, we evaluate a sequentially and a parallel CUDA-accelerated Markov De-
cision Process Markov Decision Process (MDP) based scheme and a fast greedy heuristics
algorithm to optimize the problem of vehicular task placement with both IEEE 1609.4 and
opportunistically available V2I of AAA scheme. We derive the system reward of Vehicular
Cloud Computing VCC by considering the overall utilization of the virtualized resources
of the distributed Vehicular Clouds (VCs) as well as the optimality of the solution of
placement of the vehicular Bag-of-Tasks (BOTs)
We present our vision to create such a beneficial link by designing a multimodal
scheme for object detection, recognition, and mapping based on the fusion of stereo camera
frames, point cloud Velodyne LIDAR scans, and Vehicle-to-Vehicle (V2V) Basic Safety
Messages Basic Safety Messages (BSMs) exchanges using VANET protocols. Exploiting
the high similarities in the underlying manifold properties of the three data sets, and their
high neighborhood correlation, the proposed scheme employs semi-supervised manifold
alignment to merge the key features of rich texture descriptions of objects from 2D images,
depth and distance between objects provided by 3D point cloud, and awareness of self-
declared vehicles from BSMs’ 3D information including the ones not seen by camera and
LIDAR. The proposed scheme is applied to create joint pixel-to-point-cloud and pixel-
to-V2V correspondences of objects in frames from the KITTI Vision Benchmark Suite,
using a semi-supervised manifold alignment, to achieve camera-LIDAR and camera-V2V
mapping of their recognized objects. We present the alignment accuracy results over 2
different driving sequences and illustrate the additional acquired knowledge of objects
from the various input modalities. We also study the effect of the number of neighbors
employed in the alignment process on the alignment accuracy.

Herein, is the reported synthesis and utilization of redox-active arylazoformamide (AAF) ligands in palladium(II) precatalysts for the Suzuki-Miyaura cross-coupling reaction. Complexes were formed from 2 equiv of an AAF ligand with Pd(II)Cl2 in an appropriate solvent to create the square planar (AAF)2PdCl2 precatalyst. A thorough investigation of aryl bromides and arylboronic acids found that 1.0 mol % precatalyst with cesium carbonate (Cs2CO3) as base, 1,4-dioxane as solvent at 90 °C for 24 h allowed for excellent conversions to the biphenyl products (over 20 examples). To highlight the AAF ligand class, a set of comparison reactions were performed with redox-active arylazothioformamide ligands, i.e., an (ATF)2PdCl2 complex, other commercial palladium(II) complexes, and a Ni(II)Cl2 arylazoformamide coordination complex2. The (AAF)2PdCl2 complexes outperformed all of others tested. Mechanistically, it is proposed that the AAF ligand singly reduces to antiferromagnetically couple to the palladium(I) complex as a transmetalation intermediate. Ni-based precatalysts were found to be inactive for the studied Suzuki-Miyaura reaction. Overall, these ligand systems offer a unique look into redox-active palladium cross-coupling reactions as well as being phosphine-free and high yielding.

In 2020, a three-day Tribal Nation Building in Higher Education Convening was held at the University of Idaho. This gathering brought together Indigenous professors, administrators, and allied collaborators to engage in deep discussion of nation-building as a framework for supporting Indigenous nationhood in higher education. This white paper details the findings of the dialogue drawing on a qualitative survey, over eighteen hours of discussion-based audio conversation between participants, and artifacts created by participants during the convening. The participating nation builders centered their engagements in Tribal Nation building in higher education around four salient concepts: decolonization, sovereignty, importance of place, and context specificity. Speaking from this foundational worldview, convening findings underscored collective struggles and successes in Tribal nation building efforts with and through institutions of higher education. We outline the struggles as emerging from six distinct but connected barriers to Tribal nation building: Bureaucratic obstruction; Gatekeeping; Leadership instability; Institutional isolation; Limited Indigenous faculty; Insufficient investment and prioritization. While consistent across contexts, barriers manifest differently determined by local context. Details about successes in Tribal nation building in higher education provided evidence to identify seven principles, or pillars, for higher educational systems that directly attends to the health and wellbeing of Tribal Nations and Native peoples: Representation, Community Building, Tribal Nation Involvement, Collaboration, Committed Leadership, Student Involvement, and Sustainability. We conclude this report with the seven principles as tangible structures to build strong university-Tribal relationships toward investing in thriving Tribal nations and changing the conditions of higher education for Native peoples.